plotPrior: Check priors used in ease of use brms functions

In pcvr: Plant Phenotyping and Bayesian Statistics

Check priors used in ease of use brms functions

Description

Check priors used in ease of use brms functions

Usage

plotPrior(priors, type = "density", n = 200, t = 25)

Arguments

priors	A named list of means for prior distributions. This takes the same input as the prior argument of growthSS. Alternatively, if given the output of growthSS this will preform a prior predictive check and return a plot from growthPlot of that check ignoring all other arguments. Note that all priors must be proper in that case (non-flat) and the fit is likely to be strange looking due to how thick tailed the default priors from growthSS are.
type	Either "density", the default, or a model as would be specified in growthSS or growthSim such as "logistic", "gompertz", "monomolecular", "exponential", "linear", "power law", "double logistic", or "double gompertz". If this is a model type then n draws from the prior will be simulated as growth trendlines and densities will be plotted on margins for some distributions.
n	Numeric, if type is a model then how many draws from the prior should be simulated?
t	Numeric, time passed to growthSim. Defaults to 25 (the growthSim default).

Value

A named list of plots showing prior distributions that growthSS would use, optionally with a plot of simulated growth curves using draws from those priors.

See Also

barg for Bayesian model reporting metrics, growthSim for simulating data using similar specification.

Examples

set.seed(123)
priors <- list("A" = c(100, 130), "B" = c(10, 8), "C" = c(0.2, 0.1))
plotPrior(priors)

plotPrior(priors, "gompertz")[[1]]

pcvr documentation built on April 16, 2025, 5:12 p.m.