Constructor for GPF
GPF.Rd
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
-
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
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) }