Package 'ecotoxicology'

Title: Methods for Ecotoxicology
Description: Implementation of the EPA's Ecological Exposure Research Division (EERD) tools (discontinued in 1999) for Probit and Trimmed Spearman-Karber Analysis. Probit and Spearman-Karber methods from Finney's book "Probit analysis a statistical treatment of the sigmoid response curve" with options for most accurate results or identical results to the book. Probit and all the tables from Finney's book (code-generated, not copied) with the generating functions included. Control correction: Abbott, Schneider-Orelli, Henderson-Tilton, Sun-Shepard. Toxicity scales: Horsfall-Barratt, Archer, Gauhl-Stover, Fullerton-Olsen, etc.
Authors: Jose Gama [aut, cre, trl]
Maintainer: Jose Gama <[email protected]>
License: GPL (>= 3)
Version: 1.0.1
Built: 2024-11-19 06:46:16 UTC
Source: CRAN

Help Index

Calculate corrected efficacy % with Abbott's formula

Description

Returns the corrected efficacy % with Abbott's formula

Usage

AdjustAbbott(smoothedObservedProportion, ps0 = smoothedObservedProportion[1],
  p1 = 1)

Arguments

smoothedObservedProportion

numeric vector, treated population
ps0

numeric vector, control
p1

numeric vector, percentage 0 to1 or 0 to 100 (p1=1 or P1=100)

Value

the corrected efficacy %

Author(s)

Jose Gama

Source

ehabsoft, last accessed 2015 http://www.ehabsoft.com/ldpline/onlinecontrol.htm

References

Puntener W., 1981 Manual for field trials in plant protection second edition. Agricultural Division, Ciba-Geigy Limited.

Examples

#same result as example on Short-term Methods for Estimating the Chronic Toxicity of
#Effluents and Receiving Waters to Freshwater Organisms.TABLE J1. page 312
data(SheepsheadMinnow40SK)
IsMonotonicallyIncreasing(SheepsheadMinnow40SK[,2]/40)
mydata <- cbind(SheepsheadMinnow40SK,
  MakeMonotonicallyIncreasing(cbind(rep(40,6),SheepsheadMinnow40SK[,2])))
AdjustAbbott(mydata[,3])

Calculate corrected efficacy % with Henderson-Tilton's formula

Description

Returns the corrected efficacy % with Henderson-Tilton's formula

Usage

AdjustHendersonTilton(smoothedObservedProportion,
  ps0 = smoothedObservedProportion[1], p1 = 1)

Arguments

smoothedObservedProportion

numeric vector, treated population
ps0

numeric vector, control
p1

numeric vector, percentage 0 to1 or 0 to 100 (p1=1 or P1=100)

Value

the corrected efficacy %

Author(s)

Jose Gama

Source

ehabsoft, last accessed 2015 http://www.ehabsoft.com/ldpline/onlinecontrol.htm

References

Puntener W., 1981 Manual for field trials in plant protection second edition. Agricultural Division, Ciba-Geigy Limited.

Calculate corrected efficacy % with Schneider-Orelli's formula

Description

Returns the corrected efficacy % with Schneider-Orelli's formula

Usage

AdjustSchneiderOrelli(smoothedObservedProportion,
  ps0 = smoothedObservedProportion[1], p1 = 1)

Arguments

smoothedObservedProportion

numeric vector, treated population
ps0

numeric vector, control
p1

numeric vector, percentage 0 to1 or 0 to 100 (p1=1 or P1=100)

Value

the corrected efficacy %

Author(s)

Jose Gama

Source

ehabsoft, last accessed 2015 http://www.ehabsoft.com/ldpline/onlinecontrol.htm

References

Puntener W., 1981 Manual for field trials in plant protection second edition. Agricultural Division, Ciba-Geigy Limited.

Calculate corrected efficacy % with Sun-Shepard's formula

Description

Returns the corrected efficacy % with Sun-Shepard's formula

Usage

AdjustSunShepard(smoothedObservedProportion,
  ps0 = smoothedObservedProportion[1], p1 = 1)

Arguments

smoothedObservedProportion

numeric vector, treated population
ps0

numeric vector, control
p1

numeric vector, percentage 0 to1 or 0 to 100 (p1=1 or P1=100)

Value

the corrected efficacy %

Author(s)

Jose Gama

Source

ehabsoft, last accessed 2015 http://www.ehabsoft.com/ldpline/onlinecontrol.htm

References

Puntener W., 1981 Manual for field trials in plant protection second edition. Agricultural Division, Ciba-Geigy Limited.

data on the toxicity to Aphis rumicis of an ether extract of Derris malaccensis

Description

data on the toxicity to Aphis rumicis of an ether extract of Derris malaccensis

Usage

AphisRumicisDerrisMalaccensis

Details

  • concentration. concentration

  • n. number of insects

  • r. number of observed affected

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. pp 238. Cambridge University Press

Martin, J. T ., 1940 The problem of the evaluation of rotenone-containing plants. V. The relative toxicities of different species of derris. Ann. Appl. Biol. 27, 274-94.

Convert Arcsin values to percentages

Description

Converts Arcsin values to percentages

Usage

ArcsinToPercentage(myarcsin)

Arguments

myarcsin

numeric vector

Value

percentages

Author(s)

Jose Gama

References

Statistical tests for significance, accessed October 2015 http://archive.bio.ed.ac.uk/jdeacon/statistics/tress4.html

Examples

a<-c(.1,.5,1:10,50,96,97,98,99.5,99.99,99.999,99.9999)
b<-PercentageToProbit(a)
d<-ProbitToPercentage(b)
e<-PercentageToArcsin(d)
f<-ArcsinToPercentage(e)

Calculate LC50 from a matrix with 3 columns: concentration, number of exposed subjects and number of deaths

Description

Returns the LC50 from a matrix with 3 columns: concentration, number of exposed subjects and number of deaths

Usage

CalculateLC50(matrixConcExpoResp)

Arguments

matrixConcExpoResp

numeric vector

Value

the LC50

Author(s)

Jose Gama

References

Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977. Trimmed spearman-karber method for estimating median Lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 11(7): 714-719; Correction 12(4):417 (1978).

Examples

#Data from the example on page 5:
#Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977.
#Trimmed spearman-karber method for estimating median
#Lethal concentrations in toxicity bioassays.
#Environ. Sci. Technol. 11(7): 714-719;
#Correction 12(4):417 (1978).
concentration<-c(.5,1,2,4,8)
exposed<-c(10,10,10,10,10)
mortality<-c(0,2,4,9,10)
CalculateLC50(cbind(concentration, exposed, mortality))

Calculate LC for N between 0 (LC0) and 100 (LC100)

Description

Returns the LC for n between 0 and 100

Usage

CalculateLCn(x, n, r, N = 50)

Arguments

x

numeric, log concentration
n

numeric, number of insects
r

numeric, number of observed affected
N

numeric, Lethal Concentration "N"

Value

the LC for n between 0 and 100

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Critical Values of Dunnett's t Statistic

Description

Critical Values of Dunnett's t Statistic, Two-Tailed Comparisons

Usage

Dunnett.t.Statistic

Details

Critical Values of Dunnett's t Statistic - data columns

  • df. Degress of freedom.

  • alpha. significance level.

  • 2. k=2, Number of Treatment Means, Including Control.

  • 3. k=3, Number of Treatment Means, Including Control.

  • 4. k=4, Number of Treatment Means, Including Control.

  • 5. k=5, Number of Treatment Means, Including Control.

  • 6. k=6, Number of Treatment Means, Including Control.

  • 7. k=7, Number of Treatment Means, Including Control.

  • 8. k=8, Number of Treatment Means, Including Control.

  • 9. k=9, Number of Treatment Means, Including Control.

  • 10. k=10, Number of Treatment Means, Including Control.

Author(s)

Jose Gama

References

C. W. Dunnett, 1964. New tables for multiple comparisons with a control. Biometrics 20. 482–491.

Inverse error function

Description

Returns the inverse error function

Usage

erfinv(x)

Arguments

x

numeric vector

Value

the inverse error function

Author(s)

Jose Gama

References

Abramowitz and Stegun 29.2.29 http://stat.ethz.ch/R-manual/R-devel/library/stats/html/Normal.html

Examples

erfinv(1:10)

Generate table I from Finney1964 "Transformation of percentages to probits"

Description

Generates table I from Finney1964 "Transformation of percentages to probits"

Usage

GenTableIFinney1964()

Value

table I from Finney1964 "Transformation of percentages to probits"

  • Percentage. Percentage.

  • Col0.0. Column for 0.0

  • Col0.1. Column for 0.1

  • Col0.2. Column for 0.2

  • Col0.3. Column for 0.3

  • Col0.4. Column for 0.4

  • Col0.5. Column for 0.5

  • Col0.6. Column for 0.6

  • Col0.7. Column for 0.7

  • Col0.8. Column for 0.8

  • Col0.9. Column for 0.9

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableIFinney1964()

Generate table II from Finney1964 "The weighting coefficient and Q/Z"

Description

Generates table II from Finney1964 "The weighting coefficient and Q/Z"

Usage

GenTableIIFinney1964()

Value

table II from Finney1964 "The weighting coefficient and Q/Z"

  • Y. expected probit

  • Q/Z.

  • C=0. 0

  • C=1. 1 ...

  • C=89. 89

  • C=90. 90

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableIIFinney1964()

Generate table III from Finney1964 "Maximum and minimum working probits and range"

Description

Generates table III from Finney1964 "Maximum and minimum working probits and range"

Usage

GenTableIIIFinney1964()

Value

table III from Finney1964 "Maximum and minimum working probits and range"

  • Ymin. Minimum working probit - expected

  • Y0. Minimum working probit - Y0 = Y-P/Z

  • Yrange. Range 1/Z

  • Y100. Maximum working probit - Y100 = Y+Q/Z

  • Ymax. Maximum working probit - expected

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableIIIFinney1964()

Generate table IV from Finney1964 "Working probits"

Description

Generates table IV from Finney1964 "Working probits"

Usage

GenTableIVFinney1964()

Value

table IV from Finney1964 "Working probits"

  • Kill

  • Col2 Expected probit 2.0

  • Col2.1 Expected probit 2.1 ...

  • Col7.8 Expected probit 7.8

  • Col7.9 Expected probit 7.9

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableIVFinney1964()

Generate table IX from Finney1964 "Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling"

Description

Generates table IX from Finney1964 "Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling"

Usage

GenTableIXFinney1964()

Value

table IX from Finney1964 "Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling"

  • Y. Expected probit

  • MinWorkProbit. Minimum working probit

  • Range. Range 1/Z

  • WeightingCoef. Weighting Coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableIXFinney1964()

Generate table V from Finney1964 "The Probability, P, the Ordinate, Z, and Z^2"

Description

Generates table V from Finney1964 "The Probability, P, the Ordinate, Z, and Z^2"

Usage

GenTableVFinney1964()

Value

table V from Finney1964 "The Probability, P, the Ordinate, Z, and Z^2"

  • Y. Expected probit

  • P. Probability P of expected probit

  • Z. Ordinate to the normal distribution corresponding to the probability P

  • Z^2. Z^2

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableVFinney1964()

Generate table VI from Finney1964 "Distribution of chi^2"

Description

Generates table VI from Finney1964 "Distribution of chi^2"

Usage

GenTableVIFinney1964()

Value

table VI from Finney1964 "Distribution of chi^2"

  • Deg.freedom. Degrees of freedom

  • 0.9. Probability 0.9

  • 0.7. Probability 0.7

  • 0.5. Probability 0.5

  • 0.3. Probability 0.3

  • 0.1. Probability 0.1

  • 0.05. Probability 0.05

  • 0.02. Probability 0.02

  • 0.01. Probability 0.01

  • 0.001. Probability 0.001

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableVIFinney1964()

Generate table VII from Finney1964 "Distribution of t"

Description

Generates table VII from Finney1964 "Distribution of t"

Usage

GenTableVIIFinney1964()

Value

table VII from Finney1964 "Distribution of t"

  • Deg.freedom. Degrees of freedom

  • 0.9. Probability 0.9

  • 0.7. Probability 0.7

  • 0.5. Probability 0.5

  • 0.3. Probability 0.3

  • 0.1. Probability 0.1

  • 0.05. Probability 0.05

  • 0.02. Probability 0.02

  • 0.01. Probability 0.01

  • 0.001. Probability 0.001

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableVIIFinney1964()

Generate table VIII from Finney1964 "The Weighting Coefficient in Wadley's Problem"

Description

Generates table VIII from Finney1964 "The Weighting Coefficient in Wadley's Problem"

Usage

GenTableVIIIFinney1964()

Value

table VIII from Finney1964 "The Weighting Coefficient in Wadley's Problem"

  • Y. Expected probit

  • w. Weighting Coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

GenTableVIIIFinney1964()

Determine if a series is monotonically decreasing

Description

Returns TRUE if all proportions are in a monotonically decreasing sequence

Usage

IsMonotonicallyDecreasing(p)

Arguments

p

numeric vector

Value

True is the series is monotonically decreasing

Author(s)

Jose Gama

References

Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977. Trimmed spearman-karber method for estimating median Lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 11(7): 714-719; Correction 12(4):417 (1978).

Examples

IsMonotonicallyDecreasing(1:10)
IsMonotonicallyDecreasing(6:2)
IsMonotonicallyDecreasing(c(1,3,2))

Determine if a series is monotonically increasing

Description

Returns TRUE if all proportions are in a monotonically increasing sequence

Usage

IsMonotonicallyIncreasing(p)

Arguments

p

numeric vector

Value

True is the series is monotonically increasing

Author(s)

Jose Gama

References

Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977. Trimmed spearman-karber method for estimating median Lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 11(7): 714-719; Correction 12(4):417 (1978).

Examples

#Data from the example on page 8:
#Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977.
#Trimmed spearman-karber method for estimating median
#Lethal concentrations in toxicity bioassays.
#Environ. Sci. Technol. 11(7): 714-719;
#Correction 12(4):417 (1978).
concentration<-c(1.1,2.3,4.5,8.8,17.1)
exposed<-c(10,10,9,10,10)
mortality<-c(1,5,4,2,7)
p<-mortality/exposed
x<-log(concentration)
IsMonotonicallyIncreasing(p)

Make monotonically decreasing sequence

Description

Returns a monotonically decreasing sequence

Usage

MakeMonotonicallyDecreasing(matrixExpoResp)

Arguments

matrixExpoResp

numeric vector or matrix

Value

monotonically decreasing sequence

Author(s)

Jose Gama

References

Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977. Trimmed spearman-karber method for estimating median Lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 11(7): 714-719; Correction 12(4):417 (1978).

Smoothed Mortality Proportion (monotonically increasing sequence)

Description

Returns the Smoothed Mortality Proportion (monotonically increasing sequence)

Usage

MakeMonotonicallyIncreasing(matrixExpoResp)

Arguments

matrixExpoResp

numeric vector or matrix

Value

The Smoothed Mortality Proportion (monotonically increasing sequence)

Author(s)

Jose Gama

References

Hamilton, m.a., R.c. Russo, and r.v. Thurston, 1977. Trimmed spearman-karber method for estimating median Lethal concentrations in toxicity bioassays. Environ. Sci. Technol. 11(7): 714-719; Correction 12(4):417 (1978).

Convert percentages to Arcsin values

Description

Converts percentages to Arcsin values

Usage

PercentageToArcsin(mypercentage)

Arguments

mypercentage

numeric vector

Value

Arcsin values

Author(s)

Jose Gama

References

Statistical tests for significance, accessed October 2015 http://archive.bio.ed.ac.uk/jdeacon/statistics/tress4.html

Examples

a<-c(.1,.5,1:10,50,96,97,98,99.5,99.99,99.999,99.9999)
b<-PercentageToProbit(a)
d<-ProbitToPercentage(b)
e<-PercentageToArcsin(d)

Convert percentages to Probit values

Description

Converts percentages to Probit values

Usage

PercentageToProbit(mypercentage)

Arguments

mypercentage

numeric vector

Value

Probit values

Author(s)

Jose Gama

References

Statistical tests for significance, accessed October 2015 http://archive.bio.ed.ac.uk/jdeacon/statistics/tress4.html

Examples

a<-c(.1,.5,1:10,50,96,97,98,99.5,99.99,99.999,99.9999)
b<-PercentageToProbit(a)

Approximate Standard Error of dosage

Description

Approximate Standard Error of dosage

Usage

ProbitApproxStandardErrorOfDosage(b, Snw)

Arguments

b

numeric, rate of increase of probit value per unit increase in x
Snw

numeric, sum of nw

Value

Approximate Standard Error of dosage

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Estimate the column for Chi calculation

Description

Estimates the column for Chi calculation

Usage

ProbitChi(r, n, P)

Arguments

r

numeric vector, number of observed affected
n

numeric vector, number of insects
P

numeric vector, Probability P of expected probit

Value

numeric vector

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Probit estimation similar to the EPA's Ecological Exposure Research Division (EERD) tool

Description

Probit estimation similar to the EPA's Ecological Exposure Research Division (EERD) tool

Usage

ProbitEPA(toxData, retData = FALSE, showOutput = TRUE)

Arguments

toxData

numeric matrix, matrix with concentration, n ,r columns
retData

logic, return the results in a list
showOutput

logic, show results in the console

Value

Probit estimation regression

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Probit Fiducial Limits

Description

Probit Fiducial Limits

Usage

ProbitFiducialLimits(Vm, m, tPercent = 5, roundFinney = FALSE)

Arguments

Vm

numeric, variance of the logarithm
m

numeric, logLD50
tPercent

numeric, probability level
roundFinney

logic, round as in Finney's book

Value

Probit Fiducial Limits

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Probit estimation regression with Finney's method

Description

Probit estimation regression with Finney's method

Usage

ProbitFinney(toxData, tPercent = 5, showPlot = FALSE, roundFinney = FALSE)

Arguments

toxData

numeric matrix, matrix with concentration, n ,r columns
tPercent

numeric, probability level
showPlot

logic, show regression line - plot
roundFinney

logic, round as in Finney's book

Value

Probit estimation regression

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Probit regression line

Description

Probit regression line

Usage

ProbitRegression(x, n, r, adjAbbot = FALSE, roundFinney = FALSE)

Arguments

x

numeric, log concentration
n

numeric, number of insects
r

numeric, number of observed affected
adjAbbot

logic, use Abbot adjustment
roundFinney

logic, round as in Finney's book

Value

Probit regression line a+bx

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Standard Error of dosage

Description

Standard Error of dosage

Usage

ProbitStandardErrorOfDosage(varianceDosage)

Arguments

varianceDosage

numeric, Variance of dosage

Value

Standard Error of dosage

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Standard Error of rate of increase of probit value per unit increase in x

Description

Standard Error of rate of increase of probit value per unit increase in x

Usage

ProbitStandardErrorRate(n, w, x, xbar)

Arguments

n

numeric, number of insects
w

numeric, weighting coefficients
x

numeric, log concentration
xbar

numeric, mean dosage

Value

Standard Error of rate of increase of probit value per unit increase in x

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Convert Probit values to percentages

Description

Converts Probit values to percentages

Usage

ProbitToPercentage(myprobit)

Arguments

myprobit

numeric vector

Value

percentages

Author(s)

Jose Gama

References

Statistical tests for significance, accessed October 2015 http://archive.bio.ed.ac.uk/jdeacon/statistics/tress4.html

Examples

a<-c(.1,.5,1:10,50,96,97,98,99.5,99.99,99.999,99.9999)
b<-PercentageToProbit(a)
d<-ProbitToPercentage(b)

Probit value "g"

Description

Probit value "g"

Usage

ProbitVALUEg(b, n, w, x, xbar, tPercent)

Arguments

b

numeric, rate of increase of probit value per unit increase in x
n

numeric, number of insects
w

numeric, weighting coefficients
x

numeric, log concentration
xbar

numeric, mean dosage
tPercent

numeric, probability level

Value

Probit value "g"

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Variance of dosage

Description

Variance of dosage

Usage

ProbitVarianceDosage(b, m, n, w, x, xbar)

Arguments

b

numeric, rate of increase of probit value per unit increase in x
m

numeric, dosage
n

numeric, number of insects
w

numeric, weighting coefficients
x

numeric, log concentration
xbar

numeric, mean dosage

Value

Variance of dosage

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Variance of rate of increase of probit value per unit increase in x

Description

Variance of rate of increase of probit value per unit increase in x

Usage

ProbitVarianceRate(n, w, x, xbar)

Arguments

n

numeric, number of insects
w

numeric, weighting coefficients
x

numeric, log concentration
xbar

numeric, mean dosage

Value

Variance of rate of increase of probit value per unit increase in x

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Calculate weighting coefficient from expected probit

Description

Returns the weighting coefficient from expected probit

Usage

Probitw(Y, C = 0)

Arguments

Y

numeric, expected probit
C

numeric, proportion of natural mortality

Value

the weighting coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press. Formula 6.3.

Examples

# Example from page 90 of Finney 1964:
# expected probit Y = 6.2, control mortality C = 59%
Y <- 6.2
C <- 0.59
# weighting coefficient = 0.141
Probitw(Y,C)

Calculate the weighting coefficient

Description

Returns the weighting coefficient

Usage

ProbitWeightingCoef(Z, Q, P, C)

Arguments

Z

numeric, ordinate to the normal distribution corresponding to the probability P
Q

numeric, 1-P
P

numeric, Probability P of expected probit
C

numeric, proportion of natural mortality

Value

the weighting coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press. Formula 6.3.

Examples

# Example from page 90 of Finney 1964:
# expected probit Y = 6.2, control mortality C = 59%
Y <- 6.2
C <- 0.59
P <- pnorm(Y-5)
Q <- 1-P
Z <- ProbitZ(Y)
# weighting coefficient = 0.141
ProbitWeightingCoef(Z,Q,P,C)

Calculate working probit

Description

Returns the working probit

Usage

ProbitWorkingP(Y, p)

Arguments

Y

numeric, expected probit
p

numeric, kill percentage

Value

the working probit

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

# Example from page 50 of Finney 1964:
# kill p = 72.3%, expected probit Y = 6.2
Y <- 6.2
p <- 72.3/100
# working probit = 5.366
ProbitWorkingP(Y,p)

Calculate the ordinate to the normal distribution corresponding to the probability P

Description

Returns the ordinate to the normal distribution corresponding to the probability P

Usage

ProbitZ(Y)

Arguments

Y

numeric, expected probit

Value

the ordinate to the normal distribution corresponding to the probability P

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press. Formula 3.5.

Examples

# expected probit Y = 6.2
Y <- 6.2
ProbitZ(Y)

Calculate the ordinate to the normal distribution corresponding to the probability P, exactly like Finney's

Description

Returns the ordinate to the normal distribution corresponding to the probability P with the exact same results as Finney's

Usage

ProbitZ4dec(Y)

Arguments

Y

numeric, expected probit

Value

the ordinate to the normal distribution corresponding to the probability P

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press. Formula 3.5.

Examples

# expected probit Y = 6.2
Y <- 6.2
ProbitZ4dec(Y)

Archer Scale for assessment of leaf damage

Description

Archer Scale for assessment of leaf damage

Usage

ScaleArcher(percentAffected)

Arguments

percentAffected

numeric vector

Value

Archer Scale for assessment of leaf damage

Author(s)

Jose Gama

References

Archer, T.L., 1987 Techniques for screening maize for resistance to mites. pp.178-183. In: Mihn, J.A., Wiseman, B.R. and Davis, F.M. (Eds.). Proceedings of the International symposium on methodologies for developing host plant resistance to maize insects. CIMMYT, Mexico.

Gauhl’s modification of Stover’s severity scoring system

Description

Gauhl’s modification of Stover’s severity scoring system

Usage

ScaleGauhlStover(percentShowingSymptoms)

Arguments

percentShowingSymptoms

numeric, proportion of the leaf area showing symptoms

Value

Gauhl-Stover scale

Author(s)

Jose Gama

References

Gauhl F., 1994 Epidemiology and ecology of black Sigatoka (Mycosphaerella fijiensis Morlet) on plantain and banana (Musa spp.) in Costa Rica, Central America. INIBAP, Montpellier, France. 120pp).

Horsfall-Barratt Scale for Measuring Plant Disease

Description

Horsfall-Barratt Scale for Measuring Plant Disease

Usage

ScaleHorsfallBarratt(percentAffected)

Arguments

percentAffected

numeric vector

Value

Horsfall-Barratt Scale for Measuring Plant Disease

Author(s)

Jose Gama

References

Horsfall, J. G.; Barratt, R. W., 1945 An Improved Grading System for Measuring Plant Disease. Phytopathology.

Mortality data from a fathead minnow larval survival and growth test (40 organisms per concentration)

Description

Mortality data from a fathead minnow larval survival and growth test (40 organisms per concentration)

Usage

SheepsheadMinnow40SK

Details

Mortality data from a fathead minnow larval survival and growth test - data columns

  • Concentration. Concentration.

  • Mortality. Mortality

Author(s)

Jose Gama

References

USEPA, 2002 Short-term Methods for Estimating the Chronic Toxicity of Effluents and Receiving Waters to Freshwater Organisms. 4th Edition,USEPA,Office of Water,October 2002,EPA 821-R-02-013 TABLE J1. pp 312

Spearman Karber estimation

Description

Spearman Karber estimation

Usage

SpearmanKarber(toxData, N, retData = FALSE, showOutput = TRUE,
  showPlot = TRUE)

Arguments

toxData

numeric matrix, matrix with concentration, n ,r columns
N

numeric, number of organisms
retData

logic, return the results in a list
showOutput

logic, show results in the console
showPlot

logic, show regression line - plot

Value

Spearman Karber estimation

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Transformation of Percentages to Probits, table I of Finney, 1964

Description

Transformation of Percentages to Probits, table I of Finney, 1964

Usage

Table1Finney1964

Details

Transformation of Percentages to Probits - data columns

  • Percentage. Percentage.

  • Col0.0. Column for 0.0

  • Col0.1. Column for 0.1

  • Col0.2. Column for 0.2

  • Col0.3. Column for 0.3

  • Col0.4. Column for 0.4

  • Col0.5. Column for 0.5

  • Col0.6. Column for 0.6

  • Col0.7. Column for 0.7

  • Col0.8. Column for 0.8

  • Col0.9. Column for 0.9

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

The Weighting Coefficient and Q/Z, table II of Finney, 1964

Description

The Weighting Coefficient and Q/Z, table II of Finney, 1964

Usage

Table2Finney1964

Details

The Weighting Coefficient and Q/Z - data columns

  • Y. expected probit

  • Q/Z.

  • C=0. 0

  • C=1. 1 ...

  • C=89. 89

  • C=90. 90

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Maximum and Minimum working probits and Range, table III of Finney, 1964

Description

Maximum and Minimum working probits and Range, table III of Finney, 1964

Usage

Table3Finney1964

Details

Maximum and Minimum working probits and Range - data columns

  • Ymin. Minimum working probit - expected

  • Y0. Minimum working probit - Y0 = Y-P/Z

  • Yrange. Range 1/Z

  • Y100. Maximum working probit - Y100 = Y+Q/Z

  • Ymax. Maximum working probit - expected

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Working probits, table IV of Finney, 1964

Description

Working probits, table IV of Finney, 1964

Usage

Table4Finney1964

Details

Working probits - data columns

  • Kill

  • Col2 Expected probit 2.0

  • Col2.1 Expected probit 2.1 ...

  • Col7.8 Expected probit 7.8

  • Col7.9 Expected probit 7.9

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

The Probability, P, the Ordinate, Z, and Z^2, table V of Finney, 1964

Description

Probability, P, the Ordinate, Z, and Z^2, table V of Finney, 1964

Usage

Table5Finney1964

Details

The Probability, P, the Ordinate, Z, and Z^2 - data columns

  • Y. Expected probit

  • P. Probability P of expected probit

  • Z. Ordinate to the normal distribution corresponding to the probability P

  • Z^2. Z^2

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

The Weighting Coefficient in Wadley's Problem, table VIII of Finney, 1964

Description

The Weighting Coefficient in Wadley's Problem, table VIII of Finney, 1964

Usage

Table8Finney1964

Details

The Weighting Coefficient in Wadley's Problem - data columns

  • Y. Expected probit

  • w. Weighting Coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling, table IX of Finney, 1964

Description

Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling, table IX of Finney, 1964

Usage

Table9Finney1964

Details

Minimum Working Probit, Range, and Weighting Coefficient for Inverse Sampling - data columns

  • Y. Expected probit

  • MinWorkProbit. Minimum working probit

  • Range. Range 1/Z

  • WeightingCoef. Weighting Coefficient

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Generate table 26 from Finney1964 "The Function for Planning Tests of Mixtures of Two Poisons"

Description

Generates table 26 from Finney1964 "The Function for Planning Tests of Mixtures of Two Poisons"

Usage

TestMix2poisons()

Value

table 26 from Finney1964 "The Function for Planning Tests of Mixtures of Two Poisons"

  • rho. toxicity

  • 0.1. distance 0.1 log rho in the left of the probit regression line ...

  • 0.9. distance 0.9 log rho in the left of the probit regression line

Author(s)

Jose Gama

References

Finney D. J., 1964 Probit analysis: a statistical treatment of the sigmoid response curve. Cambridge University Press

Examples

TestMix2poisons()

Trimmed Spearman-Karber method, as per Hamilton and EPA

Description

Returns the Trimmed Spearman-Karber (TSK) method, as per Hamilton and EPA

Usage

TSK(x, r, n, A = 0, conf = 0.95)

Arguments

x

numeric vector
r

numeric vector
n

numeric vector
A

numeric vector
conf

numeric vector

Value

mu=mu,gsd=gsd,left=left,right=right

Author(s)

Jose Gama

References

Hamilton,M.A.,Russo,R.L.,Thurston,R.V.,1977. Trimmed Spearman–Karber method for estimating median lethal concentrations. Environ. Sci. Tech. 11,714–719.

Examples

x<-c(15.54,20.47,27.92,35.98,55.52)
n1<-c(20,20,20,19,20)
r<-c(0,0,0,5.26,100)/100*n1
n<-c(20,20,20,19,20)
TSK(x,r,n)

WAAPP Pest Count scoring system

Description

WAAPP Pest Count scoring system

Usage

WAAPPpestCount(percentLeafDamage)

Arguments

percentLeafDamage

numeric, percentage of leaf damage

Value

WAAPP Pest Count Score

Author(s)

Jose Gama

References

Environmental Protection Agency Chemicals Control And Managemenet Centre (ACCRA), 2012 Protocols for the biological evaluation of pesticides on Selected crops grown in both the humid and sahel regions of West africa. West Africa Agriculture Productivity Programme (WAAPP).