| Type: | Package |
| Title: | Methods for Ecotoxicology |
| Version: | 1.0.1 |
| Encoding: | UTF-8 |
| 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. |
| License: | GPL (≥ 3) |
| Depends: | R (≥ 2.10) |
| Author: | Jose Gama [aut, cre, trl] |
| Maintainer: | Jose Gama <rxprtgama@gmail.com> |
| Repository: | CRAN |
| Repository/R-Forge/Project: | ecotoxicology |
| Repository/R-Forge/Revision: | 4 |
| Repository/R-Forge/DateTimeStamp: | 2015-10-14 09:20:55 |
| Date/Publication: | 2015-10-14 12:25:39 |
| NeedsCompilation: | no |
| Packaged: | 2015-10-14 09:25:24 UTC; rforge |
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.
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 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)
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)
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
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)
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()
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).
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)
Internal ecotoxicology functions
Description
Ignore these.