dprior: Density and Random Number Generation for a Join Prior...

In ggdmcPrior: Prior Probability Functions of the Standard and Truncated Distribution

Density and Random Number Generation for a Join Prior Distribution

Description

dprior computes the log-density of a joint prior distribution at a given set of parameter values. rprior generates random samples from the same joint prior specification.

Usage

dprior(p_prior_r, parameters_r)

rprior(p_prior_r, n = 1L)

Arguments

p_prior_r	A list specifying the prior distribution, typically constructed using BuildPrior.
parameters_r	For dprior: A numeric vector of parameter values at which the prior log-density should be evaluated.
n	For rprior: Integer specifying the number of random samples to generate (default is 1).

Details

These functions implement the core computations for evaluating and sampling from a joint prior distribution specified via BuildPrior:

• dprior: Evaluates the log-density of the joint prior at the given parameter values.

• rprior: Draws independent samples from the specified joint prior.

The joint prior may include truncated normal, beta, gamma, and other common distributions, possibly bounded by user-specified lower and upper limits.

Value

dprior

A numeric vector of log-density values.

rprior

A numeric matrix of dimension n × nparameter, containing samples from the prior distribution. Each row is one sample.

Examples

p0 <- c(A = 0.15, B = 0.45, mean_v = 2.25, sd_v = 0.15, t0 = 0.2)
p1 <- rep(0.1, 5)
p_prior <- BuildPrior(
    p0 = p0,
    p1 = p1,
    lower = rep(NA, 5),
    upper = rep(NA, 5),
    dist = rep("tnorm", 5),
    log_p = rep(TRUE, 5)
)

# Evaluate log-density
parameters <- seq(0.1, 0.5, by = 0.1)
res0 <- dprior(p_prior, parameters)
res1 <- dnorm(parameters, p0, 0.1, TRUE)
print(res0)
print(res1)

# Generate samples from the prior
res2 <- rprior(p_prior, 1)
res3 <- rprior(p_prior, 2)
print(res2)
print(res3)

ggdmcPrior documentation built on Aug. 8, 2025, 7:13 p.m.