Constructor for GPF

Just to help reminding the coders which elements are needed.

GPF(filename, estimates, uncertainty_correlation = data.frame())

Arguments

filename

Path to the GPF-file. # [] Can it be NULL or otherwise empty? Ask Venelin...
estimates

data.frame(PARAMETER, VALUE , othercols...) as specified in the book
uncertainty_correlation

data.frame(PARAMETER, CORRELATIONVALUES...)

Value

GPF

Details

In the estimates-sheet, the following columns are required:

  • PARAMETER: Names of parameters. c("ka", "beta_ka(WT0)", "corr(ka, CL)")

  • TYPE: Use of paramter. Not used internally but useful for the overview. c("MODEL PARAMETER", "COVARIATE")

  • VALUE: Value of parameter in linear scale

  • VALUE.RSE.PERCENT: sigma/VALUE \* 100

  • IIV: Omega (standard deviation) of random effects in "linear scale". See details for some practical examples.

  • IIV.RSE.PERCENT

  • TRANSFORMATION: One of c("N", "L", "G", NA). Can be NA only for corr, beta and error parameters

  • UNIT: Not used for sampling but highly recommended

  • COV.FORMULA: Formula for covariate transformation

  • NAME: Verbose description of the parameter

  • COV.REFERENCE: Reference value of the covariate

  • COMMENT: Ad libitum

Some practical examples you might encounter

  1. You have parameter c(ka = 2) with transformation "L" and the corresponding diagonal entry in your random effects vcov matrix is 0.4.

    • What do you put in IIV? Answer: IIV = sqrt(0.4).

    • How does the final value of an indparam look? Answer: The final indparam = exp(log(2) + rnorm(1,0,sqrt(0.4)))

See also

General Parameter Format

Other GPF helpers: addIIVCov_toGPF(), imputeTYPEcol_GPF()

Other GPF generating and I/O: addIIVCov_toGPF(), combineGPF(), export_GPF(), generate_GPFFromIQRnlmeProject(), generate_GPFFromProjectInfoList(), generate_GPFFromProjectInfo(), load_GPF(), read_GPFFromCSV(), read_GPFFromXLS()

Examples


if (FALSE) {
m <- IQRmodel(system.file("examples/GPFExamples/model_1cpt_linear_abs1.txt", package = "IQRtools"))
xls <- generate_GPFfromIQRmodel(m)
est <- xls$estimates
uc <- xls$uncertainty_correlation

# Generate xls without the uncertainty correlation matrix
xls_new <- GPF(NULL, # Only needed internally for I/O
                           estimates = est)
}