Package 'epade'

Title:	Easy Plots
Description:	A collection of nice plotting functions directly from a data.frame with limited customisation possibilities.
Authors:	Andreas Schulz
Maintainer:	Andreas Schulz <[email protected]>
License:	GPL (>= 2)
Version:	0.5.1
Built:	2024-11-13 06:40:50 UTC
Source:	CRAN

This package is a collection of statistical plots. They are aimed at making fast overview plots from a data frame without elaborate preparations of data. It is my first R package. The main motivation for making it was to learn R. At the moment there is no error protection. Be careful if you use any of the statistical tests in the plots, since they do not necessarily make sense.

Details

Package:	epade
Title:	Easy Plots
Type:	Package
Version:	0.5.1
Date:	2022-10-25
Depends:	plotrix, R (>= 2.12)
Suggests:	survival
License:	GPL (>= 2)
LazyLoad:	yes

Author(s)

Andreas Schulz
Maintainer: <[email protected]>

Bar plot

Description

A function to draw a barplot

Usage

bar.plot.ade(x, y=NULL, z=NULL, data=NULL,
             vnames.x=NULL, vnames.y=NULL, vnames.z=NULL,
             btext=NULL, b=NULL, b2=0.5, v=NULL, h=NULL, gradient=FALSE,
             xlab="", ylab="", main="", ylim=NULL,
             yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             alpha=NULL, beside=TRUE, legendon="topright", wall=0,
             lhoriz=NULL, prozent=FALSE, ploc=0, form="r", border=TRUE,
             density=NULL, angle=NULL, density2=NULL, angle2=NULL, fill=NULL,
             lwd=1, lty=1, blwd=1, blty=1)
bar.plot.ade(x, y=NULL, z=NULL, data=NULL,
             vnames.x=NULL, vnames.y=NULL, vnames.z=NULL,
             btext=NULL, b=NULL, b2=0.5, v=NULL, h=NULL, gradient=FALSE,
             xlab="", ylab="", main="", ylim=NULL,
             yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             alpha=NULL, beside=TRUE, legendon="topright", wall=0,
             lhoriz=NULL, prozent=FALSE, ploc=0, form="r", border=TRUE,
             density=NULL, angle=NULL, density2=NULL, angle2=NULL, fill=NULL,
             lwd=1, lty=1, blwd=1, blty=1)

Arguments

`x`	a factor a string with the name of the factor variable in the data.frame a formula x~y or x~y+z a table
`y`	second factor a string with the name of second factor in the data.frame
`z`	third factor a string with the name of thirds factor in the data.frame
`data`	a data.frame
`vnames.x`	a vector of character strings with labels for the levels of x
`vnames.y`	a vector of character strings with labels for the levels of y
`vnames.z`	a vector of character strings with labels for the levels of z
`btext`	logical asking whether to draw p-values from chisq test a vector of character strings with test to draw over the bars
`b`	width of bars in [0, 1]
`b2`	depth of 3d bars in [0, 1]
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`gradient`	logical asking whether to draw a color gradient
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`ylim`	the y limits (y1, y2) of the plot
`yticks`	the number of ticks on the y axis
`col`	color for the bars representing levels of y
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	colors for the lines to shading bars, a vector is possible
`alpha`	a parameter in [0, 1] for semi-transparency of bars
`beside`	logical asking whether to draw bars beside or on top
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" "none" This places the legend on the inside of the plot frame at the given location. To locate 2 legends you can give a vector of 2 keywords.
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`lhoriz`	logical asking whether to draw legend horizontal
`prozent`	logical asking whether to draw percents on bars
`ploc`	Position of percents 0: middle 1, bottom 2: over 3: top 4: under
`form`	a single keyword from: 'r': Rects 'c', 3D Rects 'z': Zylinders (not working well)
`border`	logical asking whether to draw borders os bars
`density`	first density for shading lines, in lines per inch.
`angle`	first angle (in degrees) for the shading lines.
`density2`	second density for shading lines, in lines per inch.
`angle2`	second angle (in degrees) for the shading lines.
`fill`	fill color for bars if used density, because the col parameter will be used for color of the shading lines.
`lwd`	width for shading lines
`lty`	linetype for shading lines
`blwd`	width for bar-borders
`blty`	linetype for bar-borders

Examples

x<- round(runif(1000, 0.5, 10.5))
bar.plot.ade(x, btext='Uniform distribution', gradient=TRUE)
x<-rbinom(1000, 1, 0.75)
y<-rbinom(1000, 1, 0.30)
z<-rbinom(1000, 1, 0.50)
bar.plot.ade(x,y,z)
bar.plot.ade(x,y,z, wall=4, form='c', main='Bar-Plot')
x<- round(runif(1000, 0.5, 10.5))
bar.plot.ade(x, btext='Uniform distribution', gradient=TRUE)
x<-rbinom(1000, 1, 0.75)
y<-rbinom(1000, 1, 0.30)
z<-rbinom(1000, 1, 0.50)
bar.plot.ade(x,y,z)
bar.plot.ade(x,y,z, wall=4, form='c', main='Bar-Plot')

weighted Bar plot

Description

A function to draw a weighted or unweighted barplot

Usage

bar.plot.wtd(x, y=NULL, z=NULL, w=NULL, data=NULL,
             vnames.x=NULL, vnames.y=NULL, vnames.z=NULL,
             btext=NULL, cutz=F, zperc=NULL,
             b=NULL, b2=0.5, v=NULL, h=NULL, gradient=FALSE,
             xlab="", ylab="", main="", ylim=NULL,
             yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             alpha=NULL, beside=TRUE, legendon="topright", wall=0,
             lhoriz=NULL, prozent=FALSE, ploc=0, form="r", border=TRUE,
             density=NULL, angle=NULL, density2=NULL, angle2=NULL, fill=NULL,
             lwd=1, lty=1, blwd=1, blty=1)
bar.plot.wtd(x, y=NULL, z=NULL, w=NULL, data=NULL,
             vnames.x=NULL, vnames.y=NULL, vnames.z=NULL,
             btext=NULL, cutz=F, zperc=NULL,
             b=NULL, b2=0.5, v=NULL, h=NULL, gradient=FALSE,
             xlab="", ylab="", main="", ylim=NULL,
             yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             alpha=NULL, beside=TRUE, legendon="topright", wall=0,
             lhoriz=NULL, prozent=FALSE, ploc=0, form="r", border=TRUE,
             density=NULL, angle=NULL, density2=NULL, angle2=NULL, fill=NULL,
             lwd=1, lty=1, blwd=1, blty=1)

Arguments

`x`	a factor a string with the name of the factor variable in the data.frame a formula x~y or x~y+z a table
`y`	second factor a string with the name of second factor in the data.frame
`z`	third factor a string with the name of thirds factor in the data.frame
`w`	a vector of weights a string with the name of weight variable in the data.frame
`data`	a data.frame
`vnames.x`	a vector of character strings with labels for the levels of x
`vnames.y`	a vector of character strings with labels for the levels of y
`vnames.z`	a vector of character strings with labels for the levels of z
`btext`	logical asking whether to draw p-values from chisq test a vector of character strings with test to draw over the bars
`cutz`	logical asking whether to use z variable to split bars or to calculate prozent of positive only.
`zperc`	a single keyword from: "overall" "rows" "cols" "zells" What percentages from z should be calculated?
`b`	width of bars in [0, 1]
`b2`	depth of 3d bars in [0, 1]
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`gradient`	logical asking whether to draw a color gradient
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`ylim`	the y limits (y1, y2) of the plot
`yticks`	the number of ticks on the y axis
`col`	color for the bars representing levels of y
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	colors for the lines to shading bars, a vector is possible
`alpha`	a parameter in [0, 1] for semi-transparency of bars
`beside`	logical asking whether to draw bars beside or on top
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" "none" This places the legend on the inside of the plot frame at the given location. To locate 2 legends you can give a vector of 2 keywords.
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`lhoriz`	logical asking whether to draw legend horizontal
`prozent`	logical asking whether to draw percents on bars
`ploc`	Position of percents 0: middle 1, bottom 2: over 3: top 4: under
`form`	a single keyword from: 'r': Rects 'c', 3D Rects 'z': Zylinders (not working well)
`border`	logical asking whether to draw borders os bars
`density`	first density for shading lines, in lines per inch.
`angle`	first angle (in degrees) for the shading lines.
`density2`	second density for shading lines, in lines per inch.
`angle2`	second angle (in degrees) for the shading lines.
`fill`	fill color for bars if used density, because the col parameter will be used for color of the shading lines.
`lwd`	width for shading lines
`lty`	linetype for shading lines
`blwd`	width for bar-borders
`blty`	linetype for bar-borders

Examples

x<-rbinom(1000, 1, 0.75)
y<-rbinom(1000, 1, 0.30)
z<-rbinom(1000, 1, 0.50)
w<-abs(rnorm(1000))
bar.plot.wtd(x,y,z, w)
bar.plot.wtd(x,y,z, w, wall=4, form='c', main='Bar-Plot')
x<-rbinom(1000, 1, 0.75)
y<-rbinom(1000, 1, 0.30)
z<-rbinom(1000, 1, 0.50)
w<-abs(rnorm(1000))
bar.plot.wtd(x,y,z, w)
bar.plot.wtd(x,y,z, w, wall=4, form='c', main='Bar-Plot')

3D Bar-Plot

Description

Draw pseudo 3d Bar-Plot

Usage

bar3d.ade(x, y=NULL, data=NULL, xw=0.5, zw=1,
          main=NULL, xlab=NULL, ylab=NULL, zlab=NULL,
          xticks=NULL, yticks=NULL, zticks=NULL,
          col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
          axes=TRUE, fgbox=TRUE, bgbox=TRUE, wall=0)
bar3d.ade(x, y=NULL, data=NULL, xw=0.5, zw=1,
          main=NULL, xlab=NULL, ylab=NULL, zlab=NULL,
          xticks=NULL, yticks=NULL, zticks=NULL,
          col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
          axes=TRUE, fgbox=TRUE, bgbox=TRUE, wall=0)

Arguments

`x`	a table or matrix a numeric vector or factor a string with the name of the variable in the data.frame a formula x~y
`y`	a numeric vector or factor a string with the name of the variable in the data.frame
`data`	data.frame if used strings of formul for x and y
`xw`	width of bars in x direction
`zw`	width of bars in z direction
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`zlab`	a title for the z axis
`xticks`	a vector of labels for the x axis
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`zticks`	a vector of labels for the z axis
`col`	a color for the bars a vector of colors a matrix of colors
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	bar edges color
`alpha`	a parameter in [0, 1] for semi-transparency of bars
`axes`	logical asking whether to plot axis
`fgbox`	logical asking whether to draw 3d box in forderground (dotted part of box)
`bgbox`	logical asking whether to draw 3d box (if FALSE, set fgbox to FALSE too)
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Examples

bar3d.ade(rpois(200,2), rpois(200,2), wall=3)
x <- seq(-16, 16, length= 48)
y <- x
f <- function(x,y) { r <- sqrt(x^2+y^2); 10 * sin(r)/r }
z <- outer(x, y, f)
z[is.na(z)] <- 1
bar3d.ade(z, wall=2, xw=1, zw=0.2, axes=FALSE, bgbox=FALSE,
xlab='', ylab='', zlab='', alpha=1, col='lavender')
bar3d.ade(rpois(200,2), rpois(200,2), wall=3)
x <- seq(-16, 16, length= 48)
y <- x
f <- function(x,y) { r <- sqrt(x^2+y^2); 10 * sin(r)/r }
z <- outer(x, y, f)
z[is.na(z)] <- 1
bar3d.ade(z, wall=2, xw=1, zw=0.2, axes=FALSE, bgbox=FALSE,
xlab='', ylab='', zlab='', alpha=1, col='lavender')

Bland-Altman plot

Description

Plot for assessing agreement between two methods of clinical measurement

Usage

bland.altman.ade(x, y, data=NULL, ltext=TRUE, main="Bland-Altman Plot",
                 xlab=NULL, ylab=NULL, xlim=NULL, ylim=NULL,
                 lwd=2, cex=1, pch=16, lty=c(1,2,2), xticks=NULL, yticks=NULL,
                 col=NULL, tcol=NULL, bgcol=NULL, lcol=c(4,2,2), alpha=NULL,
                 fitline=1, wall=0, v=NULL, h=NULL, span=0.75)
bland.altman.ade(x, y, data=NULL, ltext=TRUE, main="Bland-Altman Plot",
                 xlab=NULL, ylab=NULL, xlim=NULL, ylim=NULL,
                 lwd=2, cex=1, pch=16, lty=c(1,2,2), xticks=NULL, yticks=NULL,
                 col=NULL, tcol=NULL, bgcol=NULL, lcol=c(4,2,2), alpha=NULL,
                 fitline=1, wall=0, v=NULL, h=NULL, span=0.75)

Arguments

`x`	a numeric vector of first mesurement a string with the name of first mesurement in the data.frame
`y`	a numeric vector of second mesurement a string with the name of second mesurement in the data.frame
`data`	data.frame if used strings for (x,y)
`ltext`	logical asking whether to draw labels for the lines a string vector with the labels for the lines
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`lwd`	the line width
`cex`	character (or symbol) expansion: a numerical value
`pch`	plotting "character", i.e., symbol to use. This can either be a single character or an integer code for one of a set of graphics symbols.
`lty`	the line type, a vector is possible
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`col`	color of the points
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`alpha`	a parameter in [0, 1] for semi-transparency of points
`fitline`	a number between 0 and 3 to fit: 0. not fit 1. a lm regression line 2. a loess local regression line 3. a pylinomial regression line
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`span`	the span parameter for lowess curve fit (only if fitline=2)

Details

It is only a Wrapper function for scatter.ade. Ploting the Difference against the mean for both variables.

Examples

x<-rnorm(1000, 0, 3)
y<-x+rnorm(1000, 1, 0.5)
bland.altman.ade(x, y, wall=2)
x<-rnorm(1000, 0, 3)
y<-x+rnorm(1000, 1, 0.5)
bland.altman.ade(x, y, wall=2)

Boxplot

Description

Draw a box, a violin, a box-percentile and more plots for subgroups

Usage

box.plot.ade(x, group=NULL, group2=NULL, data=NULL, vnames=NULL,
             main=NULL, xlab=NULL, ylab=NULL, ylim=NULL, yticks=NULL,
             col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, pdigs=4, alpha=NULL,
             cex=1, cex.axis=1, lwd=2, h=NULL, lty=2, test=FALSE,
             varwidth=TRUE, means=FALSE, count=TRUE, zylinder=FALSE,
             twoside=TRUE, paired=FALSE, outlier=TRUE, wall=0, type='box')
box.plot.ade(x, group=NULL, group2=NULL, data=NULL, vnames=NULL,
             main=NULL, xlab=NULL, ylab=NULL, ylim=NULL, yticks=NULL,
             col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, pdigs=4, alpha=NULL,
             cex=1, cex.axis=1, lwd=2, h=NULL, lty=2, test=FALSE,
             varwidth=TRUE, means=FALSE, count=TRUE, zylinder=FALSE,
             twoside=TRUE, paired=FALSE, outlier=TRUE, wall=0, type='box')

Arguments

`x`	a numeric vector of values a character string with the name of the variable in the data.frame a formula x~group or x~group+group2
`group`	a factor to group the plots a character string with the name of the group variable in the data.frame
`group2`	a second factor to group the plots a character string with the name of the group2 variable in the data.frame
`data`	a data.frame
`vnames`	a vector of character strings with the names of groups in the legend, it can be a list of two vectors if group2 is given
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`ylim`	the y limits (y1, y2) of the plot
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`col`	color of objects (Boxes)
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`pdigs`	a number indicate how to round p-values.: see ?format.pval.ade
`alpha`	a parameter in [0, 1] for semi-transparency of objects (Boxes)
`cex`	a numeric character expansion factor for the points
`cex.axis`	a numeric character expansion factor for axis
`lwd`	the line width
`h`	the y-value(s) for horizontal line(s).
`lty`	the line type
`test`	logical asking whether to test for the difference or trend between groups a string to print before p-value. (leads to test=T)
`varwidth`	logical asking whether the boxwidth indicate the N
`means`	logical asking whether to draw points for the means
`count`	logical asking whether to shown N a string to replace N with it, if you use "?" in you string in will be replaced with N. a vector of strings to replace N with it, if you use "?" in you strings in will be replaced with N.
`zylinder`	logical asking whether to draw boxes in a zylinder style
`twoside`	logical asking whether to perform a wto sided test, or a test with direction
`paired`	logical indicating whether you want a paired test.
`outlier`	logical asking whether to draw points for outlier
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`type`	one of following: "boxplot" for a normal boxplot "violin" for a violinplot "sd" for mean and one sd interval "2sd" for mean and one, two sd intervals "percentile" for a box-percentile plot "iqr" for a IQR plot

Details

it test for difference with T-test or U-test depends on the skewness <= 1 or >1. For a trend it perform a Jonckheere-Terpstra trend test.

Examples

x<-rnorm(1000)
g<-round(runif(1000))
g2<-round(runif(1000))
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=0, count='N: ?', means=TRUE)
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=1, type="violin")
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=2, type="percentile")
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=3, type="sd")
x<-rnorm(1000)
g<-round(runif(1000))
g2<-round(runif(1000))
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=0, count='N: ?', means=TRUE)
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=1, type="violin")
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=2, type="percentile")
box.plot.ade(x, g, g2, vnames=list(c("subgroup 1","subgroup 2"),
c("group 1", "group 2")), wall=3, type="sd")

weighted Boxplot

Description

Draw a weighted Boxplot. (Beta Version)

Usage

box.plot.wtd(x, group=NULL, group2=NULL, w=NULL, data=NULL, vnames=NULL,
             main=NULL, xlab=NULL, ylab=NULL, ylim=NULL, yticks=NULL,
             col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, pdigs=4, alpha=NULL,
             cex=1, cex.axis=1, lwd=2, h=NULL, lty=2,
             varwidth=TRUE, means=FALSE, count=TRUE, zylinder=FALSE,
             outlier=TRUE, wall=0, type='box')
box.plot.wtd(x, group=NULL, group2=NULL, w=NULL, data=NULL, vnames=NULL,
             main=NULL, xlab=NULL, ylab=NULL, ylim=NULL, yticks=NULL,
             col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, pdigs=4, alpha=NULL,
             cex=1, cex.axis=1, lwd=2, h=NULL, lty=2,
             varwidth=TRUE, means=FALSE, count=TRUE, zylinder=FALSE,
             outlier=TRUE, wall=0, type='box')

Arguments

`x`	a numeric vector of values a character string with the name of the variable in the data.frame a formula x~group or x~group+group2
`group`	a factor to group the plots a character string with the name of the group variable in the data.frame
`group2`	a second factor to group the plots a character string with the name of the group2 variable in the data.frame
`w`	weights
`data`	a data.frame
`vnames`	a vector of character strings with the names of groups in the legend, it can be a list of two vectors if group2 is given
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`ylim`	the y limits (y1, y2) of the plot
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`col`	color of objects (Boxes)
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`pdigs`	a number indicate how to round p-values.: see ?format.pval.ade
`alpha`	a parameter in [0, 1] for semi-transparency of objects (Boxes)
`cex`	a numeric character expansion factor for the points
`cex.axis`	a numeric character expansion factor for axis
`lwd`	the line width
`h`	the y-value(s) for horizontal line(s).
`lty`	the line type
`varwidth`	logical asking whether the boxwidth indicate the N
`means`	logical asking whether to draw points for the means
`count`	logical asking whether to shown N a string to replace N with it, if you use "?" in you string in will be replaced with N. a vector of strings to replace N with it, if you use "?" in you strings in will be replaced with N.
`zylinder`	logical asking whether to draw boxes in a zylinder style
`outlier`	logical asking whether to draw points for outlier
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`type`	one of following: "boxplot" for a normal boxplot "sd" for mean and one sd interval "2sd" for mean and one, two sd intervals "iqr" for a IQR plot

Examples

x<-rnorm(1000)
g<-round(runif(1000))
w<-abs(rnorm(1000))
d<- data.frame(x, g, w)
box.plot.wtd('x', 'g', w='w', data=d)
x<-rnorm(1000)
g<-round(runif(1000))
w<-abs(rnorm(1000))
d<- data.frame(x, g, w)
box.plot.wtd('x', 'g', w='w', data=d)

Correlogram plot

Description

Draw a correlogram (A Correlation matrix)

Usage

correlogram.ade(vars1, vnames1="noname", vars2, vnames2="noname",
                prediktors=0, data=NULL, xlab=NULL, ylab=NULL, main=NULL,
                method="p", digits=2, pdigs=4, pvals=TRUE, bars=TRUE,
                col=NULL, tcol=NULL, bgcol=NULL, wall=0)
correlogram.ade(vars1, vnames1="noname", vars2, vnames2="noname",
                prediktors=0, data=NULL, xlab=NULL, ylab=NULL, main=NULL,
                method="p", digits=2, pdigs=4, pvals=TRUE, bars=TRUE,
                col=NULL, tcol=NULL, bgcol=NULL, wall=0)

Arguments

`vars1`	a vector of character strings with the names of variables in data.frame (rows)
`vnames1`	a vector of character strings with the labels for vars1
`vars2`	a vector of character strings with the names of variables in data.frame (cols)
`vnames2`	a vector of character strings with the labels for vars2
`prediktors`	a vector of character strings with the names of variables for adjustment (partial correlation)
`data`	a data.frame
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	a main title of the plot, it will be drawn below the plot
`method`	a single keyword from: "pearson" "spearman" "kendall" indicating which correlation coefficient is to be used.
`digits`	how many significant digits are to be used
`pdigs`	a number indicate how to round p-values.: see ?format.pval.ade
`pvals`	logical asking whether to draw p-values
`bars`	logical asking whether to draw bars
`col`	not used
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Examples

data<-rnorm(1000)
data<-as.data.frame(data)
for(i in 1:9){
eval(parse(text=paste("data$var_", i, "<- rnorm(1000)", sep='')))
eval(parse(text=paste("data$var_", i,
"[round(runif(round(runif(1, 1, 100)), 1, 1000))]<-NA", sep='')))
}
correlogram.ade(vars1=c('var_1', 'var_2', 'var_3', 'var_4', 'var_5'),
                vars2=c('var_6', 'var_7', 'var_8', 'var_9', 'var_3'),
                data=data)
data<-rnorm(1000)
data<-as.data.frame(data)
for(i in 1:9){
eval(parse(text=paste("data$var_", i, "<- rnorm(1000)", sep='')))
eval(parse(text=paste("data$var_", i,
"[round(runif(round(runif(1, 1, 100)), 1, 1000))]<-NA", sep='')))
}
correlogram.ade(vars1=c('var_1', 'var_2', 'var_3', 'var_4', 'var_5'),
                vars2=c('var_6', 'var_7', 'var_8', 'var_9', 'var_3'),
                data=data)

Curves

Description

Draw points and a line between the points

Usage

curves.ade(x, y=NULL, group=NULL, data=NULL, vnames=NULL,
          main=NULL, xlab=NULL, ylab=NULL, legendon="topright",
          xlim=NULL, ylim=NULL, lwd=1, lwd2=1, cex=1, pch=16,
          lty=1, lty2=2, col=NULL, xticks=NULL, yticks=NULL,
          tcol=NULL, bgcol=NULL, alpha=NULL, fitline=0,
          wall=0, v=NULL, h=NULL, diag=F, points=T)
curves.ade(x, y=NULL, group=NULL, data=NULL, vnames=NULL,
          main=NULL, xlab=NULL, ylab=NULL, legendon="topright",
          xlim=NULL, ylim=NULL, lwd=1, lwd2=1, cex=1, pch=16,
          lty=1, lty2=2, col=NULL, xticks=NULL, yticks=NULL,
          tcol=NULL, bgcol=NULL, alpha=NULL, fitline=0,
          wall=0, v=NULL, h=NULL, diag=F, points=T)

Arguments

`x`	a numeric vector of x coordinates for the points a string with the name of the variable in the data.frame a formula y~x or y~x+group
`y`	a numeric vector of y coordinates for the points a string with the name of the variable in the data.frame a formula y~x or y~x+group
`group`	a factor to group the points a character string with the name of the group variable in the data.frame
`data`	data.frame if used strings for (x,y,group)
`vnames`	a vector of character strings with the names of groups in the legend
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location.
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`lwd`	line width for the lines
`lwd2`	line width for the fited lines
`cex`	character (or symbol) expansion: a numerical value
`pch`	plotting "character", i.e., symbol to use. This can either be a single character or an integer code for one of a set of graphics symbols.
`lty`	the line types
`lty2`	the line type for fited lines
`col`	a vector of colors for the lines of each group
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`alpha`	a parameter in [0, 1] for semi-transparency of lines and points
`fitline`	a number between 0 and 3 to fit: 0. not fit 1. a lm regression line 2. a loess local regression line 3. a pylinomial regression line
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`diag`	logical asking whether to plot a diagonal line
`points`	logical asking whether to draw points

Details

It is only a wrapper function for scatter.ade.

Examples

x<-  -100:100
curves.ade(x, x^2, points=FALSE)
x<-  -100:100
curves.ade(x, x^2, points=FALSE)

Format a number

Description

Format an R object for pretty printing.

Usage

format_n.ade(x, digits=2, scientific=FALSE)
format_n.ade(x, digits=2, scientific=FALSE)

Arguments

`x`	a numeric value a vector of numeric values a matrix of numeric values
`digits`	how many significant digits are to be shown
`scientific`	a logical specifying whether the number should be encoded in scientific format

Value

An object of similar structure to x containing character representations of the elements of x in a common format

Examples

format_n.ade((1:10)/100)
format_n.ade((1:10)/100)

Formating p-values

Description

Format a p-value for pretty printing.

Usage

format_p.ade(x, pgits=4, digits=2)
format_p.ade(x, pgits=4, digits=2)

Arguments

`x`	a numeric p-value a vector of numeric p-values a matrix of numeric p-values
`pgits`	Number of digits after decimal for cutoff of the p-value, 4 means, all under 0.0001 will be shown like <0.0001
`digits`	how many significant digits are to be used. (bevore the cut with pgits)

Details

if used a half-integer for pgits, like 3.5 the p-value will be shown like <0.0005

Value

An object of similar structure to x containing character representations of the elements of x in a common format

Examples

format_p.ade(0.045825, 4, 3)
format_p.ade(0.000025, 4)
format_p.ade(0.000025, 3.5)
format_p.ade(0.045825, 4, 3)
format_p.ade(0.000025, 4)
format_p.ade(0.000025, 3.5)

Histogram

Description

plot multiple histograms in one plot

Usage

histogram.ade(x, group=NULL, w=NULL, data=NULL, vnames=NULL, freq=FALSE,
         breaks="Sturges", density=NULL, angle=NULL, xlab=NULL, ylab=NULL,
         main="", xlim=NULL, ylim=NULL, legendon="topright", xticks=NULL,
         col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL, lwd=1,
         kern=TRUE, norm=TRUE, bars=TRUE, wall=0, v=NULL, h=NULL, lty=2)
histogram.ade(x, group=NULL, w=NULL, data=NULL, vnames=NULL, freq=FALSE,
         breaks="Sturges", density=NULL, angle=NULL, xlab=NULL, ylab=NULL,
         main="", xlim=NULL, ylim=NULL, legendon="topright", xticks=NULL,
         col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL, lwd=1,
         kern=TRUE, norm=TRUE, bars=TRUE, wall=0, v=NULL, h=NULL, lty=2)

Arguments

`x`	a numeric vector a string with the name of the variable in the data.frame a formula x~group
`group`	a factor to make separate histogram for each class a string with the name of the group variable in the data.frame
`w`	weights for weighted histograms
`data`	a data.frame
`vnames`	a vector of character strings with the names of groups in the legend
`freq`	logical: TRUE representation of frequencies or FALSE component density.
`breaks`	a single number giving the number of cells for the histogram
`density`	the density of shading lines, in lines per inch. Set it to NA avoid shading lines with wall=0.
`angle`	the vector of slopes of shading lines, given as an angle in degrees (counter-clockwise).
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location.
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`col`	colors for each histogram
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible, only used if h or v is given
`alpha`	a parameter in [0, 1] for semi-transparency of histogram
`lwd`	the line width
`kern`	logical asking whether to draw lines for kernel density estimation
`norm`	logical asking whether to draw density from normal distribution for comparison
`bars`	logical asking whether to draw bars or only polygones of kernel density estimation
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`lty`	the line type, a vector of types is possible

Examples

g<-rbinom(1000, 1, 0.5)
x<-rnorm(1000)+g
histogram.ade(x, g, wall=3, breaks=24)
histogram.ade(x, g, wall=2, bars=FALSE)
g<-rbinom(1000, 1, 0.5)
x<-rnorm(1000)+g
histogram.ade(x, g, wall=3, breaks=24)
histogram.ade(x, g, wall=2, bars=FALSE)

Kaplan-Meier curves

Description

plot Kaplan-Meier survival curves

Usage

KM.plot.ade(time, event, group=NULL, data=NULL, vnames=NULL,
            main="Kaplan-Meier Plot", xlab="Follow-Up Time",
            ylab="Cumulative Survival", xlim=NULL, ylim=NULL, xticks=NULL,
            legendon='bottomleft', lwd=2, lty=1,
            col=NULL, tcol=NULL, bgcol=NULL, pdigs=4,
            CI=FALSE, ycut=TRUE, zenspoints=FALSE, test=FALSE, wall=0)
KM.plot.ade(time, event, group=NULL, data=NULL, vnames=NULL,
            main="Kaplan-Meier Plot", xlab="Follow-Up Time",
            ylab="Cumulative Survival", xlim=NULL, ylim=NULL, xticks=NULL,
            legendon='bottomleft', lwd=2, lty=1,
            col=NULL, tcol=NULL, bgcol=NULL, pdigs=4,
            CI=FALSE, ycut=TRUE, zenspoints=FALSE, test=FALSE, wall=0)

Arguments

`time`	a numeric vector for time a character string with the name of time variable in the data.frame
`event`	a numeric vector for event (censoring) a character string with the name of event variable in the data.frame
`group`	a factor to group the curves a character string with the name of the group variable in the data.frame
`data`	data.frame if used character string for (time,event,group)
`vnames`	a vector of character strings with the names of groups in the legend
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location.
`lwd`	the line width
`lty`	the line type
`col`	a vector of colors for each curve
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`pdigs`	a number indicate how to round p-values.: see ?format.pval.ade
`CI`	logical asking whether to plot confidence intervals
`ycut`	logical asking whether to cut the y axis, if the space is not used
`zenspoints`	logical asking whether to draw censored datapoint
`test`	logical asking whether to test for the difference between curves
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Details

The p-value comes from a logrank test

Examples

times<-  sort(abs(rnorm(1000)))
events<- round(runif(1000))
groups<- round(runif(1000, 0, 3))
KM.plot.ade(times, events,  groups, wall=2)
times<-  sort(abs(rnorm(1000)))
events<- round(runif(1000))
groups<- round(runif(1000, 0, 3))
KM.plot.ade(times, events,  groups, wall=2)

Simple function to calculate kurtosis

Description

calculate kurtosis

Usage

kurtosis.ade(x, na.rm=FALSE)
kurtosis.ade(x, na.rm=FALSE)

Arguments

`x`	a numeric vector
`na.rm`	a logical value indicating whether NA values should be stripped before the computation proceeds.

Value

a single number of kurtosis from x

Examples

x<-rnorm(1000)
kurtosis.ade(x)
x<-rnorm(1000)
kurtosis.ade(x)

Missing Value Plot

Description

Overview of missing values in a data.frame

Usage

missiogram.ade(vars=NULL, vnames=NULL, data=NULL, ints=50, nvars=50,
               xlab="ID", ylab="Variables", main="Missing Value Plot",
               ylab2="N. Missings", col=NULL, tcol=NULL, bgcol=NULL, wall=0)
missiogram.ade(vars=NULL, vnames=NULL, data=NULL, ints=50, nvars=50,
               xlab="ID", ylab="Variables", main="Missing Value Plot",
               ylab2="N. Missings", col=NULL, tcol=NULL, bgcol=NULL, wall=0)

Arguments

`vars`	a vector of character strings with names of variables in data.frame
`vnames`	a vector of character strings with labels for the variables
`data`	a data.frame, it is possible to give only the data.frame.
`ints`	a integer giving number of intervals on x axis
`nvars`	number of variables in data.frame to be shown if only the data.frame ist given
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`ylab2`	a title for the second y axis
`col`	color of the symbols
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Details

One, two or three points indicate respectively number of missing values in this section. More then 3 missing values will be shown with a semi-transparency surface over the section. No semi-transparency means, all the values are missing in this section.

Examples

data<-rnorm(1000)
data<-as.data.frame(data)
for(i in 1:20){
eval(parse(text=paste("data$var_", i, "<- rnorm(1000)", sep='')))
eval(parse(text=paste("data$var_", i,
"[round(runif(round(runif(1, 1, 100)), 1, 1000))]<-NA", sep='')))
}
missiogram.ade(data=data)
data<-rnorm(1000)
data<-as.data.frame(data)
for(i in 1:20){
eval(parse(text=paste("data$var_", i, "<- rnorm(1000)", sep='')))
eval(parse(text=paste("data$var_", i,
"[round(runif(round(runif(1, 1, 100)), 1, 1000))]<-NA", sep='')))
}
missiogram.ade(data=data)

Parallel coordinate plot

Description

Draw a parallel coordinate plot

Usage

parallel.ade(vars, vnames=NULL, data=NULL, group=NULL, ylim=NULL,
             xlab=NULL, ylab=NULL, main=NULL,
             alpha=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             scale=FALSE, desc=FALSE, means=TRUE,
             legendon="top", wall=0)
parallel.ade(vars, vnames=NULL, data=NULL, group=NULL, ylim=NULL,
             xlab=NULL, ylab=NULL, main=NULL,
             alpha=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
             scale=FALSE, desc=FALSE, means=TRUE,
             legendon="top", wall=0)

Arguments

`vars`	a list of numeric variables a vector of character strings with the names of variables in data.frame
`vnames`	a vector of character strings with the names of variables
`data`	data.frame if used character string for vars
`group`	a factor to group the lines a character string with the name of the group variable in the data.frame
`ylim`	the y limits (y1, y2) of the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`alpha`	a parameter in [0, 1] for semi-transparency of points
`col`	a vector of colors for the lines for each group or each line if not using groups
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the mean lines
`scale`	a logical specifying whether the variables will be scaled to the range of [0,1]
`desc`	a logical specifying whether the colors will be sorted decreasingly
`means`	logical asking whether to draw means
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location.
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Examples

x1<-rnorm(1000, 0, 5)
x2<-rnorm(1000, 0, 4)
x3<-rnorm(1000, 0, 3)
x4<-rnorm(1000, 0, 2)
parallel.ade(vars=list(x1, x2, x3, x4))
g<-rbinom(1000, 1, 0.5)
x1[g==1]<- x1[g==1]+8
x2[g==1]<- x2[g==1]-8
x3[g==1]<- x3[g==1]+6
x4[g==1]<- x4[g==1]-6
parallel.ade(vars=list(x1, x2, x3, x4), group=g,wall=3)
x1<-rnorm(1000, 0, 5)
x2<-rnorm(1000, 0, 4)
x3<-rnorm(1000, 0, 3)
x4<-rnorm(1000, 0, 2)
parallel.ade(vars=list(x1, x2, x3, x4))
g<-rbinom(1000, 1, 0.5)
x1[g==1]<- x1[g==1]+8
x2[g==1]<- x2[g==1]-8
x3[g==1]<- x3[g==1]+6
x4[g==1]<- x4[g==1]-6
parallel.ade(vars=list(x1, x2, x3, x4), group=g,wall=3)

Parallel set plot

Description

Plot proportions of categorical data in parallel manner

Usage

parallel.set.ade(vars, vnames=NULL, data=NULL,
                 xlab="Factors", ylab="Proportion", main=NULL,
                 col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
                 cex=NULL, wall=0, horizontal=FALSE)
parallel.set.ade(vars, vnames=NULL, data=NULL,
                 xlab="Factors", ylab="Proportion", main=NULL,
                 col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
                 cex=NULL, wall=0, horizontal=FALSE)

Arguments

`vars`	a list of factors a vector of character strings with the names of factors in data.frame
`vnames`	a vector of character strings with the names of factors
`data`	data.frame if used character string for vars
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`main`	an overall title for the plot
`col`	a vector of colors for each levels of first factor
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	a vector of colors or single color for areas where all levels are drawn
`alpha`	a parameter in [0, 1] for semi-transparency of polygons
`cex`	character expansion factor for levels printing
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`horizontal`	logical asking whether to draw the plot horizontally

Examples

x<-rbinom(1000, 1, 0.25)
y<-rbinom(1000, 1, 0.5)
z<-rbinom(1000, 1, 0.75)
parallel.set.ade(list(x,y,z), wall=2)
x<-rbinom(1000, 1, 0.25)
y<-rbinom(1000, 1, 0.5)
z<-rbinom(1000, 1, 0.75)
parallel.set.ade(list(x,y,z), wall=2)

Performance Plot

Description

Draw for all posible cutoffs, TP, FP, TN, FN, sensitivity, specificity and more.

Usage

performance.plot.ade(pred, event, data=NULL, vnames=NULL, cutoffs=NULL,
                     cutnames=NULL, main=NULL, xlab="cutoff", ylab="%",
                     xlim=NULL, xticks=12,
                     col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
                     nints=100, lty=NULL, lwd=2, stats=c(1, 2),
                     youden=TRUE, wall=0)
performance.plot.ade(pred, event, data=NULL, vnames=NULL, cutoffs=NULL,
                     cutnames=NULL, main=NULL, xlab="cutoff", ylab="%",
                     xlim=NULL, xticks=12,
                     col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
                     nints=100, lty=NULL, lwd=2, stats=c(1, 2),
                     youden=TRUE, wall=0)

Arguments

`pred`	a numeric predictor vector a string with the name of the variable in the data.frame a formula yevent~pred
`event`	a numeric event vector a string with the name of the variable in the data.frame
`data`	data.frame if used character string for (pred, event)
`vnames`	a vector of character strings with the labels for performance values in top legend
`cutoffs`	a vector of optional cutoffs, to draw vertical lines
`cutnames`	a vector of character strings with the names for optional cutoffs
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`xlim`	the x limits (x1, x2) of the plot
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`col`	a vector of 4 colors, for the 4 areas in the plot (TP, TN, FP, FN)
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`alpha`	a parameter in [0, 1] for semi-transparency of points
`nints`	number of points for the areas and curves, precision of calculation
`lty`	a vector of line types
`lwd`	the line width for all lines, cutoff lines too
`stats`	a number or vector of numbers from 1 to 4 indicate what statistics are to be drawn 1. Sensitivity 2. Specificity 3. PPV 4. NPV
`youden`	logical asking whether to plot red line for youden-index maximum
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Examples

performance.plot.ade(rnorm(100), round(runif(100)))
performance.plot.ade(rnorm(100), round(runif(100)))

Q-Q Plot

Description

Draw a simple Q-Q Plot

Usage

qq.ade(x, data=NULL, main="Q-Q Plot",
       xlab="Theoretical Quantiles", ylab="Sample Quantiles",
       xlim=NULL, ylim=NULL, lwd=1, cex=1, pch=16, lty=1,
       xticks=NULL, yticks=NULL,
       col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL, fitline=0,
       qline=TRUE, wall=0, v=NULL, h=NULL, diag=FALSE, band=FALSE, span=0.75)
qq.ade(x, data=NULL, main="Q-Q Plot",
       xlab="Theoretical Quantiles", ylab="Sample Quantiles",
       xlim=NULL, ylim=NULL, lwd=1, cex=1, pch=16, lty=1,
       xticks=NULL, yticks=NULL,
       col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL, fitline=0,
       qline=TRUE, wall=0, v=NULL, h=NULL, diag=FALSE, band=FALSE, span=0.75)

Arguments

`x`	a numeric vector a character string with the name of the variable in the data.frame
`data`	data.frame if used character string for x
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`lwd`	the line width
`cex`	character (or symbol) expansion: a numerical value
`pch`	plotting "character", i.e., symbol to use. This can either be a single character or an integer code for one of a set of graphics symbols.
`lty`	the line type
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`col`	a color for the points
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`alpha`	a parameter in [0, 1] for semi-transparency of points
`fitline`	a number between 0 and 3 to fit: 0. not fit 1. a lm regression line 2. a loess local regression line 3. a pylinomial regression line
`qline`	logical asking whether to draw a median line fitted from data between 25th and 75th percentiles only.
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`diag`	logical asking whether to plot a diagonal line
`band`	logical asking whether to plot a simulated normal band or N of iteration for band estimation
`span`	the span parameter for lowess curve fit (only if fitline=2)

Details

It is only a wrapper function for scatter.ade.

Examples

qq.ade(rnorm(1000))
qq.ade(rchisq(1000, 2), fitline=2, wall=3, col=2)
qq.ade(rnorm(1000))
qq.ade(rchisq(1000, 2), fitline=2, wall=3, col=2)

Ratio plot

Description

A Plot for varying kinds of estimators with intervals

Usage

ratio.plot.ade(M, vnames, sectext=NULL,
               main=NULL, xlab=NULL, ylab=NULL, legenlab=NULL, rlab=NULL,
               col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
               r=NULL, v=c(0,1), lty=c(1,2), xticks=18,
               hlines=TRUE, legends=TRUE, logaxe=FALSE, wall=0)
               
ratio.plot.ade(M, vnames, sectext=NULL,
               main=NULL, xlab=NULL, ylab=NULL, legenlab=NULL, rlab=NULL,
               col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
               r=NULL, v=c(0,1), lty=c(1,2), xticks=18,
               hlines=TRUE, legends=TRUE, logaxe=FALSE, wall=0)

Arguments

`M`	A matrix or a list of matrices where first column is the estimated value, second and third are lower and upper interval limits , rows are different values for comparison.
`vnames`	a vector of character strings with the names for different values (rows)
`sectext`	a secont text to be placed under the vnames, can be p-values for example
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`legenlab`	a vector of character strings with the names for groups in the legend
`rlab`	a title over the vnames
`col`	a vector of colors for the intervals in each group
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`r`	a value in (0,1), define the right space for labels.
`v`	the x-value(s) for vertical line(s).
`lty`	the line type
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`hlines`	logical asking whether to draw horizontal grid lines
`legends`	logical asking whether to draw the legend
`logaxe`	logical asking whether to use a logarithmic scale on x axis
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.

Examples

vnames<-c('Value 1', 'Value 2', 'Value 3', 'Value 4')
x<-abs(rnorm(4))
M1<-cbind(x, x-(x/2), x+(x/2))
x<-abs(rnorm(4))
M2<-cbind(x, x-(x/2), x+(x/2))
x<-abs(rnorm(4))
M3<-cbind(x, x-(x/2), x+(x/2))
ratio.plot.ade(list(M1, M2, M3), vnames=vnames, wall=3,
legenlab=c('group 1', 'group 2', 'group 3'))
vnames<-c('Value 1', 'Value 2', 'Value 3', 'Value 4')
x<-abs(rnorm(4))
M1<-cbind(x, x-(x/2), x+(x/2))
x<-abs(rnorm(4))
M2<-cbind(x, x-(x/2), x+(x/2))
x<-abs(rnorm(4))
M3<-cbind(x, x-(x/2), x+(x/2))
ratio.plot.ade(list(M1, M2, M3), vnames=vnames, wall=3,
legenlab=c('group 1', 'group 2', 'group 3'))

ROC-curves plot

Description

Function to plot ROC curves with AUC calculation

Usage

roc.plot.ade(pred, event, group=NULL, data=NULL, vnames=NULL,
             main="", xlab="1-Specificity", ylab="Sensitivity",
             digits=3, pdigs=4, lty=1, lwd=2,
             col=NULL, tcol=NULL, bgcol=NULL,
             wall=0, test=FALSE, CC=TRUE, auc=TRUE, diag=TRUE, spec=FALSE)
roc.plot.ade(pred, event, group=NULL, data=NULL, vnames=NULL,
             main="", xlab="1-Specificity", ylab="Sensitivity",
             digits=3, pdigs=4, lty=1, lwd=2,
             col=NULL, tcol=NULL, bgcol=NULL,
             wall=0, test=FALSE, CC=TRUE, auc=TRUE, diag=TRUE, spec=FALSE)

Arguments

`pred`	a list of numeric predictor variables a vector of character strings with the names of the predictors in data.frame
`event`	a numeric event variable a character strings with the names of event variable in data.frame
`group`	a factor to group the curves a character strings with the names of factor variable in data.frame
`data`	data.frame if used character string for (pred,event,group)
`vnames`	a vector of character strings with the names of groups in the legend
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`digits`	how many significant digits are to be shown for AUC
`pdigs`	a number indicate how to round p-values.: see ?format.pval.ade
`lty`	a single line type or a vector og line types
`lwd`	the line width
`col`	a vector of colors for each curve
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`test`	logical asking whether to test for the difference between curves
`CC`	logical asking whether to use complete cases for all curves
`auc`	logical asking whether to draw AUC in legend
`diag`	logical asking whether to plot a diagonal line
`spec`	logical asking whether to draw a axis for Specificity at top.

Details

if test is TRUE the function perform a DeLong-DeLong test for correlated ROC-curves

Examples

# simple curve
event<-rbinom(1000, size=1, prob=0.3)
pred <- event+rnorm(1000)
roc.plot.ade(pred, event)
# grouped
group=rbinom(1000, 1 ,0.5)
roc.plot.ade(pred, event, group, wall=2)
# comparison of two predictors
pred2 <- event+rnorm(1000, 0, 2)
roc.plot.ade(list(pred, pred2), event, test=TRUE, wall=3)
# simple curve
event<-rbinom(1000, size=1, prob=0.3)
pred <- event+rnorm(1000)
roc.plot.ade(pred, event)
# grouped
group=rbinom(1000, 1 ,0.5)
roc.plot.ade(pred, event, group, wall=2)
# comparison of two predictors
pred2 <- event+rnorm(1000, 0, 2)
roc.plot.ade(list(pred, pred2), event, test=TRUE, wall=3)

A round function

Description

round a numeric value for pretty printing.

Usage

round_n.ade(x, digits = 0)
round_n.ade(x, digits = 0)

Arguments

`x`	a numeric R object
`digits`	how many digits are to be shown after decimal?

Details

the function print zeros at the end of a number, to show the precision of rounding

Value

An object of similar structure to x containing character representations of the elements of x in a rounded format

Examples

round_n.ade(13.1415, 2)
round_n.ade(3, 3)
round_n.ade(13.1415, 2)
round_n.ade(3, 3)

Scatterplot

Description

Draw a scatter or a bubble plot

Usage

scatter.ade(x, y=NULL, group=NULL, z=NULL, data=NULL, vnames=NULL,
            main=NULL, xlab=NULL, ylab=NULL, glab=NULL, zlab=NULL,
            legendon="topright", xlim=NULL, ylim=NULL, zlim=NULL,
            lwd=1, cex=1, pch=16, lty=1,
            xticks=NULL, yticks=NULL, zticks=NULL,
            col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
            fitline=0, wall=0, v=NULL, h=NULL, diag=FALSE, span=0.75)
scatter.ade(x, y=NULL, group=NULL, z=NULL, data=NULL, vnames=NULL,
            main=NULL, xlab=NULL, ylab=NULL, glab=NULL, zlab=NULL,
            legendon="topright", xlim=NULL, ylim=NULL, zlim=NULL,
            lwd=1, cex=1, pch=16, lty=1,
            xticks=NULL, yticks=NULL, zticks=NULL,
            col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL, alpha=NULL,
            fitline=0, wall=0, v=NULL, h=NULL, diag=FALSE, span=0.75)

Arguments

`x`	a numeric vector of x coordinates for the points a character string with the name of the x variable in the data.frame a formula y~x, y~x+group or y~x+z+group
`y`	a numeric vector of y coordinates for the points a character string with the name of the y variable in the data.frame
`group`	a factor to group the points a character string with the name of the group variable in the data.frame
`z`	a numeric vector for size of the points a character string with the name of the size variable in the data.frame
`data`	data.frame if used character string for (x,y,g,z) or formula
`vnames`	a vector of character strings with the names of groups in the legend
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`glab`	a title of the legend
`zlab`	a title for the z in the second legend
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" "none" This places the legend on the inside of the plot frame at the given location. To locate 2 legends you can give a vector of 2 keywords.
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`zlim`	the z limits (z1, z2) for the size of points
`lwd`	the line width
`cex`	character (or symbol) expansion: a numerical value, dont work if z is given
`pch`	plotting "character", i.e., symbol to use. This can either be a single character or an integer code for one of a set of graphics symbols. 15, 16, 17 working well with given z.
`lty`	the line type
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`zticks`	the number os Symbols in the z legend or a vector of values for the Symbols
`col`	a vector of colors for the points for each group
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`alpha`	a parameter in [0, 1] for semi-transparency of points
`fitline`	a number between 0 and 3 to fit: 0. not fit 1. a lm regression line 2. a loess local regression line 3. a pylinomial regression line
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).
`diag`	logical asking whether to plot a diagonal line
`span`	the span parameter for lowess curve fit (only if fitline=2)

Examples

x<-rnorm(1000)
y<-rnorm(1000)
z<-rnorm(1000, 3)
g<-round(runif(1000))
# plot vs ID
scatter.ade(x, vnames=c("blue","red"), alpha=0.25, fitline=2, wall=0, lwd=2, col=4)
# Scatter plot
scatter.ade(x, y*x, g, vnames=c("blue","red"), alpha=0.25, wall=2)
# bubble plot
scatter.ade(x, y, g, z, vnames=c("blue","red"), alpha=0.25, zticks=c(1,2,3,4,5), wall=3)
x<-rnorm(1000)
y<-rnorm(1000)
z<-rnorm(1000, 3)
g<-round(runif(1000))
# plot vs ID
scatter.ade(x, vnames=c("blue","red"), alpha=0.25, fitline=2, wall=0, lwd=2, col=4)
# Scatter plot
scatter.ade(x, y*x, g, vnames=c("blue","red"), alpha=0.25, wall=2)
# bubble plot
scatter.ade(x, y, g, z, vnames=c("blue","red"), alpha=0.25, zticks=c(1,2,3,4,5), wall=3)

Simple function to calculate skewness

Description

calculate skewness

Usage

skewness.ade(x, na.rm=FALSE, w=NULL)
skewness.ade(x, na.rm=FALSE, w=NULL)

Arguments

`x`	a numeric vector
`na.rm`	a logical value indicating whether NA values should be stripped before the computation proceeds.
`w`	weights

Value

a single number of skewness from x

Examples

x<-rnorm(1000)
skewness.ade(x)
x<-rnorm(1000)
skewness.ade(x)

Tornado or population plot

Description

draw a tornado plot, it could be a population pyramid

Usage

tornado.ade(x, group=NULL, group2=NULL, data=NULL, vnames=NULL, gnames=NULL,
            gnames2=NULL, breaks=6, density=NULL, angle=NULL,
            xlab=NULL, glab=NULL, main='', legendon='topright', xticks=NULL,
            col=NULL, tcol=NULL,  bgcol=NULL, lcol=NULL, alpha=NULL,
            r=0.05, lwd=1, lty=2, wall=0, v=NULL, h=NULL)
tornado.ade(x, group=NULL, group2=NULL, data=NULL, vnames=NULL, gnames=NULL,
            gnames2=NULL, breaks=6, density=NULL, angle=NULL,
            xlab=NULL, glab=NULL, main='', legendon='topright', xticks=NULL,
            col=NULL, tcol=NULL,  bgcol=NULL, lcol=NULL, alpha=NULL,
            r=0.05, lwd=1, lty=2, wall=0, v=NULL, h=NULL)

Arguments

`x`	a numeric vector a sigle factor a string with the name of the variable in the data.frame a formula x~group+group2 a table or matrix a list of tables
`group`	a factor to separate the plot in two halves a string with the name of the factor in the data.frame nothing if x is a formula, table or list
`group2`	a factor to separate the plot in several groups a string with the name of the factor in the data.frame nothing if x is a formula, table or list
`data`	a data.frame
`vnames`	a vector of character strings with the names of groups in tornado eye
`gnames`	a vector of character strings with the names of both groups
`gnames2`	a vector of character strings with the names of groups in the legend
`breaks`	a single number giving the number of cells to separate x, works only if x is a numeric vector
`density`	the vector of density of shading bars in each group
`angle`	the vector of slopes of shading bars, given as an angle in degrees (counter-clockwise).
`xlab`	a title for the x axis
`glab`	a title for the legend
`main`	an overall title for the plot
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location.
`xticks`	the number of ticks on the x axis
`col`	colors for each group
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible, only used if h or v is given
`alpha`	a parameter in [0, 1] for semi-transparency of bars
`r`	the width of empty edge for the legend if it overlap the bars
`lwd`	the line width
`lty`	the line type, a vector of types is possible
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).

Examples

tab1<-cbind(rpois(20, 20),rpois(20, 20))
tab2<-cbind(rpois(20, 15),rpois(20, 15))
tab3<-cbind(rpois(20, 10),rpois(20, 10))
tornado.ade(list(tab1, tab2, tab3), gnames=c('Men','Women'), xlab='number')
tab1<-cbind(rpois(20, 20),rpois(20, 20))
tab2<-cbind(rpois(20, 15),rpois(20, 15))
tab3<-cbind(rpois(20, 10),rpois(20, 10))
tornado.ade(list(tab1, tab2, tab3), gnames=c('Men','Women'), xlab='number')

Plot templates (wall)

Description

A function to make look a like templates of plots for different wall parameters.

Usage

wall.ade(vnames=NULL, main=NULL, xlab=NULL, ylab=NULL, glab=NULL,
         legendon="topright", xlim=NULL, ylim=NULL, lwd=1, pch=16, lty=1,
         xticks=NULL, yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
         wall=0, v=NULL, h=NULL)
wall.ade(vnames=NULL, main=NULL, xlab=NULL, ylab=NULL, glab=NULL,
         legendon="topright", xlim=NULL, ylim=NULL, lwd=1, pch=16, lty=1,
         xticks=NULL, yticks=NULL, col=NULL, tcol=NULL, bgcol=NULL, lcol=NULL,
         wall=0, v=NULL, h=NULL)

Arguments

`vnames`	a vector of character strings with labels in the legend
`main`	an overall title for the plot
`xlab`	a title for the x axis
`ylab`	a title for the y axis
`glab`	a title of the legend
`legendon`	a single keyword from: "bottomright" "bottom" "bottomleft" "left" "topleft" "top" "topright" "right" "center" This places the legend on the inside of the plot frame at the given location. To locate 2 legends you can give a vector of 2 keywords.
`xlim`	the x limits (x1, x2) of the plot
`ylim`	the y limits (y1, y2) of the plot
`lwd`	the line width
`pch`	character or symbol in the legend
`lty`	the line type
`xticks`	the number of ticks on the x axis or a vector of exact ticks
`yticks`	the number of ticks on the y axis or a vector of exact ticks
`col`	a vector of colors for the points in the legend
`tcol`	color of the text in whole plot
`bgcol`	the background color for plot dekoration
`lcol`	color for the lines in plot, a vector of colors is possible
`wall`	a number between 0 and 6 for selection the dekoration style of the plot.
`v`	the x-value(s) for vertical line(s).
`h`	the y-value(s) for horizontal line(s).

Examples

par(ask=TRUE)
wall.ade(vnames=c('blue', 'red'), wall=0, main='Template of wall 0', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=1, main='Template of wall 1', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=2, main='Template of wall 2', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=3, main='Template of wall 3', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=4, main='Template of wall 4', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=5, main='Template of wall 5', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=6, main='Template of wall 6', xlab='x', ylab='y')
par(ask=TRUE)
wall.ade(vnames=c('blue', 'red'), wall=0, main='Template of wall 0', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=1, main='Template of wall 1', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=2, main='Template of wall 2', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=3, main='Template of wall 3', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=4, main='Template of wall 4', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=5, main='Template of wall 5', xlab='x', ylab='y')
wall.ade(vnames=c('blue', 'red'), wall=6, main='Template of wall 6', xlab='x', ylab='y')

Package 'epade'

Help Index

Easy Plots

Description

Details

Author(s)

Bar plot

Description

Usage

Arguments

See Also

Examples

weighted Bar plot

Description

Usage

Arguments

See Also

Examples

3D Bar-Plot

Description

Usage

Arguments

See Also

Examples

Bland-Altman plot

Description

Usage

Arguments

Details

See Also

Examples

Boxplot

Description

Usage

Arguments

Details

Examples

weighted Boxplot

Description

Usage

Arguments

Examples

Correlogram plot

Description

Usage

Arguments

Examples

Curves

Description

Usage

Arguments

Details

See Also

Examples

Format a number

Description

Usage

Arguments

Value

See Also

Examples

Formating p-values

Description

Usage

Arguments

Details

Value

See Also

Examples

Histogram

Description

Usage

Arguments

Examples

Kaplan-Meier curves

Description

Usage

Arguments

Details

Examples