plot_param_stats_mcmc: Plot Autocorrelation, Effective sample size, Geweke...

In pbs-assess/gfiscamutils: Provide functions for iSCAM models

Plot Autocorrelation, Effective sample size, Geweke statistic, and Heidelberger & Welch statistic histograms. This is a re-coded version of https://github.com/r4ss/r4ss/blob/bioscale/R/mcmc.nuisance.R

Description

Plot Autocorrelation, Effective sample size, Geweke statistic, and Heidelberger & Welch statistic histograms. This is a re-coded version of https://github.com/r4ss/r4ss/blob/bioscale/R/mcmc.nuisance.R

Usage

plot_param_stats_mcmc(
  model,
  col = get_shade(color = "blue", opacity = 30),
  effn_labels = FALSE,
  ylim_mult = 1,
  show_ro_loc = FALSE,
  ro_yloc = 50,
  ro_yloc_arr_start = 60,
  ro_yloc_arr_end = 30
)

Arguments

model	A model as returned by load_rds_file()
col	A color to shade the bars
effn_labels	If TRUE, add labels to the top of the bars on the effective sample size plot
ylim_mult	Multiply the maximum ylim value by this (to show labels on bars better if effn_labels is TRUE)
show_ro_loc	If TRUE, place the text "R0" over the bar in which the R0 parameter falls
ro_yloc	If show_ro_loc is TRUE, use this value as a y value for the text
ro_yloc_arr_start	If show_ro_loc is TRUE, use this value as a y value for the start of the arrow pointing to the bar where R0 is
ro_yloc_arr_end	If show_ro_loc is TRUE, use this value as a y value for the end of the arrow pointing to the bar where R0 is

Value

A barplot()

pbs-assess/gfiscamutils documentation built on Oct. 24, 2024, 1:37 p.m.