log_prior: Log-prior for pharmacokinetic parameters

In hlweeks/pkpredict: Compartment Model Implementation for Pharmacokinetic Analysis

Log-prior for pharmacokinetic parameters

Description

Evaluates the prior distribution (normal) of the log parameter vector with normally distributed error.

Usage

log_prior(
  lpr,
  mu = getOption("pkpredict.pip.default.prior")$log_pk_mean,
  sig = getOption("pkpredict.pip.default.prior")$log_pk_vcov,
  ler_mean = getOption("pkpredict.pip.default.prior")$log_err_mean,
  ler_sdev = getOption("pkpredict.pip.default.prior")$log_err_sd
)

Arguments

lpr	log-PK parameter vector with error: (lv_1, lk_10, lk_12, lk_21, ler_mean)
mu	log-mean of the PK parameter distribution
sig	log-variance-covariance matrix of the PK parameter distribution
ler_mean	log-mean of the error distribution
ler_sdev	log-standard deviation of the error distribution

Details

Parameter distributions: log(lv_1, lk_10, lk_12, lk_21) ~ N(mu, sig) log(error) ~ N(ler_mean, ler_sdev)

Value

The value of the log-prior evaluated at the specified log-parameter vector

Examples

log_prior(lpr = c(getOption("pkpredict.pip.default.prior")$log_pk_mean,
                  getOption("pkpredict.pip.default.prior")$log_err_mean))

hlweeks/pkpredict documentation built on Oct. 29, 2023, 6:08 a.m.