AutocorrelationPlot: Autocorrelation plot for model selection. Model inclusion of...

In pjnewcombe/R2BGLiMS: R interface to the java package BGLiMS (Bayesian Generalised Linear Model Selection).

Description

Generates an autocorrelation plot from a Java MCMC results class object

Usage

AutocorrelationPlot(
  results,
  plot.title = NULL,
  file = NULL,
  include.var.names.on.x.axis = TRUE,
  covariates.to.include = NULL,
  var.dictionary = NULL,
  include.post.probs = TRUE,
  cex.x.axis.ticks = 1,
  cex.y.axis.ticks = 1,
  cex.y.axis.labels = 1,
  mar.for.varnames = 8
)

Arguments

results	A R2BGLiMS_Results-class object frum running the R2BGLiMS command.
plot.title	Optionally specify a title for the plot.
file	Path to a PDF to print plot to.
include.var.names.on.x.axis	Include variable names perpendicularly below the x-axis. Turn off if it looks too crowded.
covariates.to.include	Character vector indicating a subset of covariates to include in the plot.
var.dictionary	Character vector containing a mapping of covariate names to substitutions for the plot. The names of the elements are the variable names as in the original analysis (i.e. as named in the results object).
include.post.probs	Include a barplot of posterior probabilities at the top.
cex.x.axis.ticks	Control the size of tick marks for the covariates along the X-axis. Decrease if there are many.
cex.y.axis.ticks	Control the size of tick marks for the Y-axis.
cex.y.axis.labels	Control the size of the y-labels. Decrease if these are not fitting on.
mar.for.varnames	Margin size for the bottom axis. Default is 8 so there is room for perpendicular variable names. Decrease if not using variable names.

Value

NA

Author(s)

Paul Newcombe

Examples

library(R2BGLiMS)

### --- Logistic regression with two model space prior components
# Load results from the biopsy logistic regression analysis (see R2MHRJ examples)
data(biopsyResults)
AutocorrelationPlot(biopsyResults)

pjnewcombe/R2BGLiMS documentation built on Feb. 10, 2020, 8:52 p.m.