Package 'intkrige' reference manual

Title:	A Numerical Implementation of Interval-Valued Kriging
Description:	An interval-valued extension of ordinary and simple kriging. Optimization of the function is based on a generalized interval distance. This creates a non-differentiable cost function that requires a differentiable approximation to the absolute value function. This differentiable approximation is optimized using a Newton-Raphson algorithm with a penalty function to impose the constraints. Analyses in the package are driven by the 'intsp' and 'intgrd' classes, which are interval-valued extensions of 'SpatialPointsDataFrame' and 'SpatialPixelsDataFrame' respectively. The package includes several wrappers to functions in the 'gstat' and 'sp' packages.
Authors:	Brennan Bean [aut, cre]
Maintainer:	Brennan Bean <[email protected]>
License:	MIT + file LICENSE
Version:	1.0.1
Built:	2024-11-21 06:55:32 UTC
Source:	CRAN

INTERVAL-VALUED KRIGING MODELS IN R

Description

An interval-valued extension of ordinary and simple kriging. Optimization of the function is based on a generalized interval distance. This creates a non-differentiable cost function that requires a differentiable approximation to the absolute value function. This differentiable approximation is optimized using a Newton-Raphson algorithm with a penalty function to impose the constraints. Analyses in the package are driven by the 'intsp' and 'intgrd' classes, which are interval-valued extensions of 'SpatialPointsDataFrame' and 'SpatialPixelsDataFrame' respectively. The package includes several wrappers to functions in the 'gstat' and 'sp' packages.

Functions

The package contains several generic functions such as plot, print, and summary to facilitate interval-valued analysis. In addition to these functions, the package also contains the following functions:

intkrige Make predictions on interval-valued spatial data using interval-valued kriging.
interval<- Create an interval-valued spatial object.
intvariogram Simultaneously calculate the empirical variograms for an interval-valued spatial object.
fit.intvariogram Automatically fit theoretical variograms to empirical variograms obtained from interval-valued spatial objects.
intvCheck Visualize the variogram fits for interval-valued spatial objects.
dist_cpp A c++ function to calculate great circle or Euclidean distances.

Data

utsnow An interval-valued design ground snow load dataset for Utah.
ohtemp An interval-valued 30 year mean temperature dataset for the Ohio River Basin.
ohMap A SpatialPolygons shapefile for the Ohio River Basin.

Author(s)

Brennan Bean [email protected]

Convert intgrd or intsp object back to a data frame

Description

Convert intgrd or intsp object back to a data frame

Usage

## S4 method for signature 'intgrd'
as.data.frame(x)

## S4 method for signature 'intsp'
as.data.frame(x)
## S4 method for signature 'intgrd'
as.data.frame(x)

## S4 method for signature 'intsp'
as.data.frame(x)

Arguments

`x`	An object of class `intsp` or class `intgrd`.

Value

An object of class data.frame.

Distance matrix calculation.

Description

Calculation of Euclidean or geographic distance. Based on an adaptation of rdist.earth in the fields package. Uses earth radius = 6378.388 km for great circle distance calculations.

Usage

dist_cpp(loc1, loc2, geographic)
dist_cpp(loc1, loc2, geographic)

Arguments

`loc1`	A two column matrix representing the longitude/latitude (i.e. x/y) coordinates of the first set of distances.
`loc2`	A two column matrix representing the longitude/latitude (i.e. x/y) coordinates of the second set of distances (for pairwise distance matrix set loc1 = loc2).
`geographic`	If TRUE, calculate great circle distance. If FALSE, calculate Euclidean distance.

Details

Note that while this function is still available to users. It is not actively used in the intkrige function. Instead, for user convenience, distances are calculated using distance functions in the sp package.

Value

A matrix of pairwise distances between each combination of rows from loc1 and loc2 respectively.

Examples

data(utsnow)
locs1 <- as.matrix(utsnow[, c("LONGITUDE", "LATITUDE")])
distMat <- dist_cpp(locs1, locs1, geographic = TRUE)
data(utsnow)
locs1 <- as.matrix(utsnow[, c("LONGITUDE", "LATITUDE")])
distMat <- dist_cpp(locs1, locs1, geographic = TRUE)

Extract subset of an `intsp` or `intgrd` object

Description

Extract subset of an intsp or intgrd object

Usage

## S4 method for signature 'intgrd'
x$name

## S4 replacement method for signature 'intgrd'
x$name <- value

## S4 method for signature 'intgrd,ANY,missing,missing'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'intsp'
x$name

## S4 replacement method for signature 'intsp'
x$name <- value

## S4 method for signature 'intsp,ANY,missing,missing'
x[i, j, ..., drop = TRUE]

## S4 replacement method for signature 'intsp'
x$name <- value
## S4 method for signature 'intgrd'
x$name

## S4 replacement method for signature 'intgrd'
x$name <- value

## S4 method for signature 'intgrd,ANY,missing,missing'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'intsp'
x$name

## S4 replacement method for signature 'intsp'
x$name <- value

## S4 method for signature 'intsp,ANY,missing,missing'
x[i, j, ..., drop = TRUE]

## S4 replacement method for signature 'intsp'
x$name <- value

Arguments

`x`	An object of class `intsp` or class `intgrd` from which to replace elements.
`name`	Character vector corresponding to the name of the column that will be extracted or replaced.
`value`	The new data used to replaced drop data in the desired slot.
`i`, `j`, `...`	indices specifying elements to extract or replace. See generic function documentation for details.
`drop`	The requested column that may be reassigned.

Value

An object of class intsp or intgrd.

Function to create a variogram object for interval-valued data.

Description

Function to create a variogram object for interval-valued data.

Usage

fit.intvariogram(x, models = gstat::vgm(rep("Sph", 3)), ...)
fit.intvariogram(x, models = gstat::vgm(rep("Sph", 3)), ...)

Arguments

`x`	An object of class `intvariogram`.
`models`	an object of class `variogramModelList`. The user must specify at least two variogram models to fit (for center and radius). If less than three models are specified then the method does not fit a variogram for the center/radius interaction.
`...`	Additional arguments for `fit.variogram`.

Value

A list of variograms objects from the gstat package.

Print the head of an intgrd object.

Description

This function extends print.sp by including a display and summary of the interval slot for the object.

Usage

## S3 method for class 'intgrd'
head(x, n = 6, ..., digits = getOption("digits"))
## S3 method for class 'intgrd'
head(x, n = 6, ..., digits = getOption("digits"))

Arguments

`x`	An object of class `intgrd`.
`n`	Number of rows to print to the screen.
`...`	Additional arguments to `print`.
`digits`	Determines how numeric values are printed to the screen (default from `sp` package).

Value

Prints a subset of the object observations to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the head of an `intsp` object.

Description

This function extends printing methods in the sp package by including a display and summary of the head of the interval slot for the object.

Usage

## S3 method for class 'intsp'
head(x, n = 6, ..., digits = getOption("digits"))
## S3 method for class 'intsp'
head(x, n = 6, ..., digits = getOption("digits"))

Arguments

`x`	An object of class `intsp`.
`n`	The number of rows to print to the screen.
`...`	Additional arguments to `print`.
`digits`	Determines how values are printed to the screen (default taken from sp package).

Value

Prints a subset of the object to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Function to extract the interval of an intsp or intgrd object

Description

Function to extract the interval of an intsp or intgrd object

Usage

interval(x)

## S4 method for signature 'intgrd'
interval(x)

## S4 method for signature 'intsp'
interval(x)
interval(x)

## S4 method for signature 'intgrd'
interval(x)

## S4 method for signature 'intsp'
interval(x)

Arguments

`x`	An object of class intsp or intgrd.

Value

A matrix containing the interval data.

Function to reassign the contents of the interval slot

Description

Function to reassign the contents of the interval slot

Usage

interval(x) <- value

## S4 replacement method for signature 'intgrd'
interval(x) <- value

## S4 replacement method for signature 'SpatialPixelsDataFrame'
interval(x) <- value

## S4 replacement method for signature 'intsp'
interval(x) <- value

## S4 replacement method for signature 'SpatialPointsDataFrame'
interval(x) <- value
interval(x) <- value

## S4 replacement method for signature 'intgrd'
interval(x) <- value

## S4 replacement method for signature 'SpatialPixelsDataFrame'
interval(x) <- value

## S4 replacement method for signature 'intsp'
interval(x) <- value

## S4 replacement method for signature 'SpatialPointsDataFrame'
interval(x) <- value

Arguments

`x`	An object of class intsp or intgrd.
`value`	Either a character vector of length two specifying the column names which will occupy the interval slot. Or, a matrix of two columns to fill the slot.

An interval extension of a SpatialPixelsDataFrame

Description

An interval extension of a SpatialPixelsDataFrame

Slots

interval: A matrix of two columns representing the lower and upper endpoints of an interval.

Algorithmic implementation of interval valued kriging.

Description

Function to implement the interval valued extension of ordinary and simple kriging. Includes all necessary input checks and error handling. Essentially acts as a switch function between the R and c++ versions of the algorithm.

Usage

intkrige(
  locations,
  newdata,
  models,
  formulas = list(center ~ 1, radius ~ 1),
  eta = 0.75,
  A = c(1, 1, 0),
  trend = NULL,
  thresh = 100,
  tolq = 0.001,
  maxq = 100,
  tolp = 0.001,
  maxp = 100,
  r = 1,
  useR = TRUE,
  fast = FALSE,
  weights = FALSE,
  cores = 1
)
intkrige(
  locations,
  newdata,
  models,
  formulas = list(center ~ 1, radius ~ 1),
  eta = 0.75,
  A = c(1, 1, 0),
  trend = NULL,
  thresh = 100,
  tolq = 0.001,
  maxq = 100,
  tolp = 0.001,
  maxp = 100,
  r = 1,
  useR = TRUE,
  fast = FALSE,
  weights = FALSE,
  cores = 1
)

Arguments

`locations`	An object of class intsp, specifying the prediction locations with an interval-valued response.
`newdata`	An object of class SpatialPointsDataFrame or SpatialPixelsDataFrame specifying the locations at which to predict intervals.
`models`	A list of variogram models of class vgm (see vgm) When specified, the third model represents the center/radius interaction.
`formulas`	A list of two formulas specifying the centering and scaling of the center and radius respectively. Limitations to these formulas are specified in the details.
`eta`	A growth/shrink parameter for penalty term. For simple kriging: eta > 1. For ordinary kriging: eta < 1.
`A`	vector of length three representing the weights of the generalized L2 distance: the vector of three contains the weights for the center, radius, and center/radius respectively. A = c(1, 1, 0) assumes the regular L2 distance calculation for intervals.
`trend`	If null, use ordinary kriging. When specified, represents the known mean of the stationary process and is an indication to use simple kriging.
`thresh`	Let n = length(locations). When abs(lam_i) < 1/(n*thresh), this lambda value is set to 0.
`tolq`	For a set penalty term, convergence is satisfied if max(abs(lamUp-lam)) < tolq.
`maxq`	For a set penalty term, the max number of iterations allowed for convergence.
`tolp`	When abs(sum(abs(lam)) - 1) < tolp, consider the constraints satisfied.
`maxp`	Maximum number of allowed iterations to satisfy equation constraints.
`r`	The starting value of the penalty term. Must be relatively large to ensure that the initial solution stays within the feasible region.
`useR`	If TRUE, use the R version of the algorithm. If FALSE, use the rcppArmadillo version.
`fast`	(Simple kriging only). If TRUE, allows lambdas to converge to 0 and subsets matrices accordingly. When FALSE, runs simple kriging using a barrier penalty at 0. Fast = TRUE is orders of magnitude faster than the full implementation. However, it is not recommended when input measurements are sparse as it is known to have convergence issues in these cases.
`weights`	If TRUE, return the vector kriging weights for each prediction. If false, simply return the predicted output.
`cores`	An integer (for parallel computing): specify the number of cores that will be devoted to the computation. Note that the argument 'all' will use all available cores minus one. Parallel processing is only relevant if you are predicting for more than one location. Note there is no parallel option when useR = FALSE.

Details

The formulas argument is current fairly limited in its use. For example the center argument can accept no transformations of the dependent variable. Similarly, the radius argument can accept no variable arguments as independent variables. The idea behind this limited use of formulas is that any transformations should be applied to the entire interval prior to input into interval-valued kriging. This ensures that input into the interval-valued kriging algorithm are well-defined intervals with properly ordered upper and lower endpoints. The transformation that are allowed within this function are linear shifts of the center, and linear scaling of the radius. Note that the scaling term for the radius can contain a division parameter but it must be encapsulated in parenthesis and included on the right hand side of the multiplication parameter.

Value

A matrix with 4 columns where rows correspond to the prediction locations and columns correspond to:

- center prediction

- radius predictions

- kriging prediction variance

- warning column for non-convergent optimization problem (0 - no warning, 1 - warning)

Examples

# First, define the location and elevation of interest.
# (In this case we pick coordinates of Utah State University)
templocs <- data.frame(lat = 41.745, long = -111.810, ELEVATION = 1456)
sp::coordinates(templocs) <- c("long", "lat")
sp::proj4string(templocs) <- "+proj=longlat +ellps=WGS84
+datum=WGS84 +no_defs +towgs84=0,0,0"

# Load the Utah Snow Load Data
data(utsnow)
utsnow.sp <- utsnow

# Convert to an 'intsp' object that inherits a SpatialPointsDataFrame
sp::coordinates(utsnow.sp) <- c("LONGITUDE", "LATITUDE")
sp::proj4string(utsnow.sp) <- sp::proj4string(templocs)
interval(utsnow.sp) <- c("minDL", "maxDL")
# Define the formulas we will use to define the intervals.
temp_formulas <- list(center ~ ELEVATION,
                     radius*(ELEVATION/median(ELEVATION)) ~ 1)

# Define, fit and check the variogram fits.
varios <- intvariogram(utsnow.sp,
                       formulas = temp_formulas)
varioFit <- fit.intvariogram(varios, models = gstat::vgm(c("Sph", "Sph", "Gau")))
preds <- intkrige::intkrige(locations = utsnow.sp,
newdata = templocs,
models = varioFit,
formulas = temp_formulas)

# First, define the location and elevation of interest.
# (In this case we pick coordinates of Utah State University)
templocs <- data.frame(lat = 41.745, long = -111.810, ELEVATION = 1456)
sp::coordinates(templocs) <- c("long", "lat")
sp::proj4string(templocs) <- "+proj=longlat +ellps=WGS84
+datum=WGS84 +no_defs +towgs84=0,0,0"

# Load the Utah Snow Load Data
data(utsnow)
utsnow.sp <- utsnow

# Convert to an 'intsp' object that inherits a SpatialPointsDataFrame
sp::coordinates(utsnow.sp) <- c("LONGITUDE", "LATITUDE")
sp::proj4string(utsnow.sp) <- sp::proj4string(templocs)
interval(utsnow.sp) <- c("minDL", "maxDL")
# Define the formulas we will use to define the intervals.
temp_formulas <- list(center ~ ELEVATION,
                     radius*(ELEVATION/median(ELEVATION)) ~ 1)

# Define, fit and check the variogram fits.
varios <- intvariogram(utsnow.sp,
                       formulas = temp_formulas)
varioFit <- fit.intvariogram(varios, models = gstat::vgm(c("Sph", "Sph", "Gau")))
preds <- intkrige::intkrige(locations = utsnow.sp,
newdata = templocs,
models = varioFit,
formulas = temp_formulas)

An interval extension of a SpatialPointsDataFrame

Description

An interval extension of a SpatialPointsDataFrame

Slots

interval: A matrix of two columns representing the lower and upper endpoints of an interval.

Function to fit empirical variograms for an interval-valued spatial object

Description

Function to fit empirical variograms for an interval-valued spatial object

Usage

intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)

## S4 method for signature 'intgrd'
intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)

## S4 method for signature 'intsp'
intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)
intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)

## S4 method for signature 'intgrd'
intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)

## S4 method for signature 'intsp'
intvariogram(x, formulas = list(center ~ 1, radius ~ 1), ...)

Arguments

`x`	An object of class intsp or intgrd.
`formulas`	A list of length two specifying the formulas related to the centers and radii respectively.
`...`	Additional arguments for sp::variogram().

Value

An object of class 'intvariogram' containing empirical variograms for the center, radius, and center/radius interaction.

Function to visualize the three variograms from an interval valued spatial data frame.

Description

Function to visualize the three variograms from an interval valued spatial data frame.

Usage

intvCheck(x, models, ...)
intvCheck(x, models, ...)

Arguments

`x`	An object of class `intvariogram`.
`models`	A list of fitted variogram models, typically an output of `fit.intvariogram`.
`...`	Additional arguments to `plot.gstatVariogram`.

Ohio River Basin map

Description

Ohio River Basin map

Usage

ohMap
ohMap

Format

A SpatialPolygons objects with the boundaries of the Ohio river basin. Shapefile obtained from the U.S. Geological Survey National Watershed Boundary Dataset.

30 year trimmed mean daily maximum and minimum temperatures for the Ohio river basin.

Description

Intervals are defined by the mean daily maximum and minimum temperatures for the Ohio river basin from January 1, 1988 - December 31, 2018. The 116 observations in this dataset all had at least 300 daily observations of temperature in at least 30 of the 31 considered years. The mean was calculated after trimming 10 influence of potential outliers.

Usage

ohtemp
ohtemp

Format

A data frame with 161 rows and 8 variables:

ID: The global historical climatological network (GHCN) station identifier
NAME: The GHCN station name
STATE: The two-digit designation for the state in which each station resides
LATITUDE: Latitude coordinate position
LONGITUDE: Longitude coordinate position
ELEVATION: Elevation of the measurement location (meters)
minm: The 30 year mean daily minimum temperature (tenths of degrees Celsius)
maxm: The 30 year mean daily maximum temperature (tenths of degrees Celsius)

Create an interval plot for spatial grid.

Description

Calls spplot to plot the locations, centers, and radii of an intgrd object in a single figure.

Usage

## S4 method for signature 'intgrd,missing'
plot(x, beside = TRUE, circleCol = "black", minRad = 0.25, ...)
## S4 method for signature 'intgrd,missing'
plot(x, beside = TRUE, circleCol = "black", minRad = 0.25, ...)

Arguments

`x`	An object of class `intgrd`.
`beside`	Tf true, center and radius plotted side by side if false, center and radius are plotted in a single figure with the center plotted using color and the radius plotted using circles circumscribed within each grid cell.
`circleCol`	If beside=TRUE, the color of the circles that will be circumscribed within each grid cell.
`minRad`	The minimum value of the radius in the circles drawn to represent the interval radii. Must be a number between 0 and 1 where approaching 0 results in a point being drawn in the center of the grid, while approaching 1 results in every circle being circumscribed in their respective grid cell (which is not very interesting).
`...`	Additional arguments to `spplot`.

Create an interval plot for spatial points.

Description

Calls spplot to plot the locations, centers, and radii of an interval-valued spatial data frame in a single figure.

Usage

## S4 method for signature 'intsp,missing'
plot(
  x,
  locationsOnly = FALSE,
  legend.positions = c("left", "right"),
  cuts = c(5, 5),
  radSize = c(0.1, 3),
  pch = 16,
  alpha = 0.5,
  ...
)
## S4 method for signature 'intsp,missing'
plot(
  x,
  locationsOnly = FALSE,
  legend.positions = c("left", "right"),
  cuts = c(5, 5),
  radSize = c(0.1, 3),
  pch = 16,
  alpha = 0.5,
  ...
)

Arguments

`x`	An object of class `intsp`.
`locationsOnly`	If TRUE, simply plots geographic locations.
`legend.positions`	The positions of the center and radius legend relative to the plotting window.
`cuts`	The number of ranges of values to print in the center and radius legend respectively.
`radSize`	A vector of length 2 indicating the range of point sizes to plot to visualize radii magnitudes.
`pch`	The shape of the points (see `plot`).
`alpha`	The transparency of the points.
`...`	Additional arguments to `spplot`.

Print the contents of an intgrd object

Description

This function extends print.sp by including a display and summary of the interval slot for the object.

Usage

## S3 method for class 'intgrd'
print(x, ..., digits = getOption("digits"))
## S3 method for class 'intgrd'
print(x, ..., digits = getOption("digits"))

Arguments

`x`	An object of class `intgrd`.
`...`	Additional arguments to `print`.
`digits`	Determines how numeric values are printed to the screen (default from `sp` package).

Value

Prints object to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the contents of an `intsp` object

Description

This function extends printing methods in the sp package by including a display and summary of the interval slot for the object.

Usage

## S3 method for class 'intsp'
print(x, digits = getOption("digits"), ...)
## S3 method for class 'intsp'
print(x, digits = getOption("digits"), ...)

Arguments

`x`	An object of class `intsp`.
`digits`	Determines how numbers are displayed on the screen. Default option taken from `sp` package.
`...`	Additional arguments to `print`.

Value

Prints object to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the object summary to the screen.

Description

Print the object summary to the screen.

Usage

## S3 method for class 'summary.intgrd'
print(x, ...)
## S3 method for class 'summary.intgrd'
print(x, ...)

Arguments

`x`	An object of class `intgrd`.
`...`	Additional arguments to `print`.

Value

Prints a subset of the object observations to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the object summary to the screen.

Description

Print the object summary to the screen.

Usage

## S3 method for class 'summary.intsp'
print(x, ...)
## S3 method for class 'summary.intsp'
print(x, ...)

Arguments

`x`	An object an object of class `intsp`.
`...`	Additional arguments to `print`.

Value

Prints a series of summaries to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Extension of the show function for intgrd objects

Description

Extension of the show function for intgrd objects

Usage

## S4 method for signature 'intgrd'
show(object)
## S4 method for signature 'intgrd'
show(object)

Arguments

object

and object of class intgrd

Extension of the show function for intgrd objects

Description

Extension of the show function for intgrd objects

Usage

## S4 method for signature 'intsp'
show(object)
## S4 method for signature 'intsp'
show(object)

Arguments

object

An object of class intsp.

Summarize the contents of an `intgrd` object, including special summaries for the interval slot.

Description

Summarize the contents of an intgrd object, including special summaries for the interval slot.

Usage

## S3 method for class 'intgrd'
summary(object, ...)
## S3 method for class 'intgrd'
summary(object, ...)

Arguments

`object`	An object of class `intgrd`.
`...`	Additional arguments to `summary`.

Value

Prints a summary of the object observations to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Summarize the contents of an `intsp` object, including special summaries for the interval slot.

Description

Summarize the contents of an intsp object, including special summaries for the interval slot.

Usage

## S3 method for class 'intsp'
summary(object, ...)
## S3 method for class 'intsp'
summary(object, ...)

Arguments

`object`	An object of class `intsp`.
`...`	Additional arguments to `summary`.

Value

Prints a series of summaries to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the tail of an intgrd object.

Description

This function extends print.sp by including a display and summary of the interval slot for the object.

Usage

## S3 method for class 'intgrd'
tail(x, n = 6, ..., digits = getOption("digits"))
## S3 method for class 'intgrd'
tail(x, n = 6, ..., digits = getOption("digits"))

Arguments

`x`	An object of class `intgrd`.
`n`	The number of rows to print to the screen.
`...`	Additional arguments to `tail`.
`digits`	Determines how numbers are displayed to the screen (default taken from package `sp`).

Value

Prints a subset of the object observations to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

Print the tail of an intsp object.

Description

This function extends print.sp by including a display and summary of the interval slot for the object.

Usage

## S3 method for class 'intsp'
tail(x, n = 6, ..., digits = getOption("digits"))
## S3 method for class 'intsp'
tail(x, n = 6, ..., digits = getOption("digits"))

Arguments

`x`	An object of class `intsp`.
`n`	The number of rows to print to the screen.
`...`	Additional arguments to `tail`.
`digits`	Determines how numbers are displayed (default taken from sp package).

Value

Prints a subset of the object to the screen, identical to SpatialPoints-class, as well as summary statistics for the interval slot.

An interval-valued design ground snow load dataset for Utah.

Description

A dataset containing the interval-valued data used in the analysis of Bean et. at (2019). The 415 measurement locations included in the dataset are taken from Bean et. al. (2018).

Usage

utsnow
utsnow

Format

A data frame with 415 rows and 8 variables:

STATION: The global historical climatological network (GHCN) station identifier
STATION_NAME: The GHCN station name
LATITUDE: Latitude coordinate position
LONGITUDE: Longitude coordinate position
ELEVATION: Elevation of the measurement location (meters)
minDL: The lower endpoint of the interval-valued design snow load as measured in kilopascals (kpa)
maxDL: The upper endpoint of the design snow load interval (kpa)
pointDL: The original point-valued design snow load from the 2018 Utah Snow Load Study (kpa)

Details

References

Bean B, Sun Y, Maguire M (2019). “Interval-Valued Kriging Models for Geostatistical Mapping with Uncertain Inputs.” (publication pending).

Bean B, Maguire M, Sun Y (2018). “The Utah Snow Load Study.” https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=4591&context=cee_facpub.

An interval-valued design ground snow load dataset for Utah that only considers depth to load conversions.

Description

A dataset containing the interval-valued data used in the analysis of Bean et. at (2019). The 415 measurement locations included in the dataset are taken from Bean et. al. (2018).

Usage

utsnow_dtl
utsnow_dtl

Format

A data frame with 415 rows and 8 variables:

STATION: The global historical climatological network (GHCN) station identifier
STATION_NAME: The GHCN station name
LATITUDE: Latitude coordinate position
LONGITUDE: Longitude coordinate position
ELEVATION: Elevation of the measurement location (meters)
minDL: The lower endpoint of the interval-valued design snow load as measured in kilopascals (kpa)
maxDL: The upper endpoint of the design snow load interval (kpa)
pointDL: The original point-valued design snow load from the 2018 Utah Snow Load Study (kpa)

Details

References

Bean B, Sun Y, Maguire M (2019). “Interval-Valued Kriging Models for Geostatistical Mapping with Uncertain Inputs.” (publication pending).

Bean B, Maguire M, Sun Y (2018). “The Utah Snow Load Study.” https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=4591&context=cee_facpub.

An interval-valued design ground snow load dataset for Utah that only considers depth to load conversions.

Description

A dataset containing the interval-valued data used in the analysis of Bean et. at (2019). The 415 measurement locations included in the dataset are taken from Bean et. al. (2018).

Usage

utsnow_dtl2
utsnow_dtl2

Format

A data frame with 415 rows and 8 variables:

STATION: The global historical climatological network (GHCN) station identifier
STATION_NAME: The GHCN station name
LATITUDE: Latitude coordinate position
LONGITUDE: Longitude coordinate position
ELEVATION: Elevation of the measurement location (meters)
minDL: The lower endpoint of the interval-valued design snow load as measured in kilopascals (kpa)
maxDL: The upper endpoint of the design snow load interval (kpa)
pointDL: The original point-valued design snow load from the 2018 Utah Snow Load Study (kpa)

Details

The interval valued kriging analysis described in Bean et. al. (2019) analyzes this dataset on a log scale after removing the effect of elevation. An example of predictions using this workflow are found in the README associated with this package. Note that this dataset differs from utsnow in that intervals only consider differences in depth to load conversions. This dataset differs from utsnow_dtl in that intervals are only calculated at the final step of the analysis: after finding 50 year events using all 8 depth to load conversion techniques. utsnow_dtl rather created annual intervals, only fitting distributions to two sets of maximums (the annual lower and upper bounds), rather fitting 8 sets of maximums on all the depth-to-load conversion types.

References

Bean B, Sun Y, Maguire M (2019). “Interval-Valued Kriging Models for Geostatistical Mapping with Uncertain Inputs.” (publication pending).

Bean B, Maguire M, Sun Y (2018). “The Utah Snow Load Study.” https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=4591&context=cee_facpub.

Package 'intkrige'

Help Index

INTERVAL-VALUED KRIGING MODELS IN R

Description

Functions

Data

Author(s)

Convert intgrd or intsp object back to a data frame

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Value

Distance matrix calculation.

Description

Usage

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Details

Value

Examples

Extract subset of an intsp or intgrd object

Description

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Value

Function to create a variogram object for interval-valued data.

Description

Usage

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Value

Print the head of an intgrd object.

Description

Usage

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Value

Print the head of an intsp object.

Description

Usage

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Value

Function to extract the interval of an intsp or intgrd object

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Value

Function to reassign the contents of the interval slot

Description

Usage

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An interval extension of a SpatialPixelsDataFrame

Description

Slots

Algorithmic implementation of interval valued kriging.

Description

Usage

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Details

Value

Examples

An interval extension of a SpatialPointsDataFrame

Description

Slots

Function to fit empirical variograms for an interval-valued spatial object

Description

Usage

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Value

Function to visualize the three variograms from an interval valued spatial data frame.

Description

Usage

Arguments

Ohio River Basin map

Description

Usage

Format

30 year trimmed mean daily maximum and minimum temperatures for the Ohio river basin.

Description

Usage

Format

Create an interval plot for spatial grid.

Description

Extract subset of an `intsp` or `intgrd` object

Print the head of an `intsp` object.

Print the contents of an `intsp` object

Summarize the contents of an `intgrd` object, including special summaries for the interval slot.

Summarize the contents of an `intsp` object, including special summaries for the interval slot.