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Last data update: 2014.03.03

R: Plot Diagnostics for an BAS Object

plot.bas

R Documentation

Plot Diagnostics for an BAS Object

Description

Four plots (selectable by 'which') are currently available: a plot of residuals against fitted values, Cumulative Model Probabilities, log marginal likelihoods versus model dimension, and marginal inclusion probabilities.

Usage

## S3 method for class 'bas'
plot(x, which=c(1:4),caption = c("Residuals vs Fitted",
                 "Model Probabilities", "Model Complexity",
                 "Inclusion Probabilities"),
                 panel = if (add.smooth) panel.smooth
                 else points, sub.caption = NULL, main = "", ask =
                 prod(par("mfcol")) < length(which) &&
                 dev.interactive(), ..., id.n = 3, labels.id =
                 names(residuals(x)), cex.id = 0.75, add.smooth =
                 getOption("add.smooth"), col.smooth=2,label.pos = c(4, 2))

Arguments

`x`	`bas` BMA object result of 'bas'
`which`	if a subset of the plots is required, specify a subset of the numbers '1:4'

`caption`	captions to appear above the plots
`panel`	panel function. The useful alternative to 'points', 'panel.smooth' can be chosen by 'add.smooth = TRUE'
`sub.caption`	common title-above figures if there are multiple; used as 'sub' (s.'title') otherwise. If 'NULL', as by default, a possible shortened version of `deparse(x$call)` is used
`main`	title to each plot-in addition to the above 'caption'
`ask`	logical; if 'TRUE', the user is asked before each plot, see 'par(ask=.)'
`...`	other parameters to be passed through to plotting functions
`id.n`	number of points to be labelled in each plot, starting with the most extreme
`labels.id`	vector of labels, from which the labels for extreme points will be chosen. 'NULL' uses observation numbers
`cex.id`	magnification of point labels.
`add.smooth`	logical indicating if a smoother should be added to most plots; see also 'panel' above
`col.smooth`	color passed to 'panel' function
`label.pos`	positioning of labels, for the left half and right half of the graph respectively, for plots 1-3

Details

This provides a panel of 4 plots: the first is a plot of the residuals versus fitted values under BMA. The second is a plot of the cumulative marginal likelihoods of models; if the model space cannot be enumerated then this provides some indication of whether the probabilities are leveling off. The third is a plot of log marginal likelihood versus model dimension and the fourth plot show the posterior marginal inclusion probabilities.

Author(s)

Merlise Clyde, based on plot.lm by John Maindonald and Martin Maechler

Examples

data(Hald)
hald.gprior =  bas.lm(Y~ ., data=Hald, prior="g-prior", alpha=13,
                      modelprior=beta.binomial(1,1),
                      initprobs="eplogp")

plot(hald.gprior)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(BAS)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BAS/plot.bma.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.bas
> ### Title: Plot Diagnostics for an BAS Object
> ### Aliases: plot.bas
> ### Keywords: regression
> 
> ### ** Examples
> 
> data(Hald)
> hald.gprior =  bas.lm(Y~ ., data=Hald, prior="g-prior", alpha=13,
+                       modelprior=beta.binomial(1,1),
+                       initprobs="eplogp")
> 
> plot(hald.gprior)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>