Description: Applying the global sensitivity analysis workflow to investigate the parameter uncertainty and sensitivity in physiologically based kinetic (PK) models, especially the physiologically based pharmacokinetic/toxicokinetic model with multivariate outputs. The package also provides some functions to check the convergence and sensitivity of model parameters (Hsieh et al., 2018 <doi:10.3389/fphar.2018.00588>).

Description: Applying the global sensitivity analysis workflow to investigate
the parameter uncertainty and sensitivity in physiologically based
kinetic (PK) models, especially the physiologically based
pharmacokinetic/toxicokinetic model with multivariate outputs.
The package also provides some functions to check the convergence
and sensitivity of model parameters. The workflow was first mentioned

Packaged: 2021-07-04 18:04:40 UTC; nan-hunghsieh

Imports: ggplot2, data.table, deSolve, foreach, parallel, doParallel
Suggests: covr, knitr, httk, rmarkdown, testthat

Title: Log Linear by Linear Asscociation models
Description: Fit Log Linear by Linear Association models
Packaged: Thu Jul 26 16:27:05 2007; fenghong

Title: Log Linear by Linear Association models and Rasch family models
Description: Fit Log Linear by Linear Association models and Rasch family models by pseudolikelihood estimation
Packaged: 2014-01-10 12:58:28 UTC; zhushanli

Package: pla
Type: Package
Title: Parallel Line Assays
Version: 0.1
Date: 2015-08-18
Author: Jens Henrik Badsberg
Depends: R (>= 3.1.0), methods
Maintainer: Jens Henrik Badsberg <pla2015@badsberg.eu>
Description: Parallel Line Assays: Completely randomized design,
Randomized Block design, and Latin squares design.
Balanced data are fitted as described in the Ph.Eur.
In the presence of missing values complete data analysis can be
performed (with computation of Fieller's confidence intervals for
the estimated potency), or imputation of values can be applied.
The package contains a script such that a pdf-document with a
report of an analysis of an assay can be produced from an input file
with data of the assay. Here no knowledge of R is needed by the user.
License: GPL (>= 2)
Packaged: 2015-08-18 21:58:53 UTC; Jens Henrik
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-08-19 00:18:25