logitHyperPars: Convert mean and standard deviation into logit-normal...
In TestDesign: Optimal Test Design Approach to Fixed and Adaptive Test Construction
View source: R/bayes_functions.R
logitHyperPars R Documentation
Convert mean and standard deviation into logit-normal distribution parameters
Description
logitHyperPars is a function for calculating parameters for a logit-normal distribution, such that the distribution yields desired mean and standard deviation.
Used for sampling the c-parameter.
Usage
logitHyperPars(mean, sd)
Arguments
mean
the desired mean.
sd
the desired standard deviation.
Value
logitHyperPars returns two values. These can be directly supplied to rlogitnorm.
Examples
pars <- logitHyperPars(0.2, 0.1)
x <- logitnorm::rlogitnorm(1000000, pars[1], pars[2])
mean(x) # close to 0.2
sd(x) # close to 0.1
TestDesign documentation built on Feb. 16, 2023, 7:19 p.m.
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View source: R/bayes_functions.R
| logitHyperPars | R Documentation |
Convert mean and standard deviation into logit-normal distribution parameters
Description
logitHyperPars is a function for calculating parameters for a logit-normal distribution, such that the distribution yields desired mean and standard deviation.
Used for sampling the c-parameter.
Usage
logitHyperPars(mean, sd)
Arguments
mean |
the desired mean. |
sd |
the desired standard deviation. |
Value
logitHyperPars returns two values. These can be directly supplied to rlogitnorm.
Examples
pars <- logitHyperPars(0.2, 0.1) x <- logitnorm::rlogitnorm(1000000, pars[1], pars[2]) mean(x) # close to 0.2 sd(x) # close to 0.1
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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