coda (version 0.10-1)

trellisplots: Trellis plots for mcmc objects

Description

These methods use the Trellis framework as implemented in the lattice package to produce space-conserving diagnostic plots from "mcmc" and "mcmc.list" objects. The xyplot methods produce trace plots. The densityplot methods and qqmath methods produce empirical density and probability plots. The levelplot method depicts the correlation of the series. The acfplot methods plot the auto-correlation in the series.

Usage

## S3 method for class 'mcmc':
densityplot(x,
             outer, aspect = "xy",
             default.scales = list(relation = "free"),
             start = 1, thin = 1,
             main = attr(x, "title"),
             xlab = "",
             plot.points = "rug",
             ...,
             subset)
## S3 method for class 'mcmc.list':
densityplot(x,
             outer = FALSE, groups = !outer,
             aspect = "xy",
             default.scales = list(relation = "free"),
             start = 1, thin = 1,
             main = attr(x, "title"),
             xlab = "",
             plot.points = "rug",
             ...,
             subset)
## S3 method for class 'mcmc':
levelplot(x, main = attr(x, "title"),
             start = 1, thin = 1,
             ...,
             xlab = "", ylab = "",
             cuts = 10, at,
             col.regions = topo.colors(100),
             subset)
## S3 method for class 'mcmc':
qqmath(x,
             outer, aspect = "xy",
             default.scales = list(y = list(relation = "free")),
             prepanel = prepanel.qqmathline,
             start = 1, thin = 1,
             main = attr(x, "title"),
             ylab = "",
             ...,
             subset)
## S3 method for class 'mcmc.list':
qqmath(x,
             outer = FALSE, groups = !outer,
             aspect = "xy",
             default.scales = list(y = list(relation = "free")),
             prepanel = prepanel.qqmathline,
             start = 1, thin = 1,
             main = attr(x, "title"),
             ylab = "",
             ...,
             subset)
## S3 method for class 'mcmc':
xyplot(x,
             outer, layout = c(1, ncol(x)),
             default.scales = list(y = list(relation = "free")),
             type = 'l',
             start = 1, thin = 1,
             ylab = "", 
             xlab = "Iteration number",
             main = attr(x, "title"),
             ...,
             subset)
## S3 method for class 'mcmc.list':
xyplot(x, outer = FALSE, groups = !outer,
             aspect = "xy", layout = c(1, ncol(x[[1]])),
             default.scales = list(y = list(relation = "free")),
             type = 'l',
             start = 1, thin = 1,
             main = attr(x, "title"),
             ylab = "",
             ...,
             subset)
acfplot(x, ...)
## S3 method for class 'mcmc':
acfplot(x, outer,
             prepanel, panel, 
             type = 'h',
             aspect = "xy",
             start = 1, thin = 1,
             lag.max = NULL,
             ylab = "Autocorrelation",
             xlab = "Lag",
             main = attr(x, "title"),
             ...,
             subset)
## S3 method for class 'mcmc.list':
acfplot(x, outer = FALSE, groups = !outer,
             prepanel, panel,
             type = if (groups) 'b' else 'h',
             aspect = "xy",
             start = 1, thin = 1,
             lag.max = NULL,
             ylab = "Autocorrelation",
             xlab = "Lag",
             main = attr(x, "title"),
             ...,
             subset)

Arguments

x

an "mcmc" or "mcmc.list" object.

outer

for the "mcmc.list" methods, a logical flag to control whether multiple runs of a series are displayed in the same panel (they are if FALSE, not if TRUE). If specified in the "mcmc" methods,

groups

for the "mcmc.list" methods, a logical flag to control whether the underlying lattice call will be supplied a groups arguments indicating which run a data point originated from. The panel function is res

aspect

controls the physical aspect ratio of the panel. See xyplot for details. The default for these methods is chosen carefully - check what the default plot looks like before changing

default.scales

this parameter provides a reasonable default value of the scales parameter for the method. It is unlikely that a user will wish to change this parameter. Pass a value for scales (see

type

a character vector that determines if lines, points, etc. are drawn on the panel. The default values for the methods are carefully chosen. See panel.xyplot for possibl

thin

an optional thinning interval that is applied before the plot is drawn.

start

an optional value for the starting point within the series. Values before the starting point are considered part of the "burn-in" of the series and dropped.

plot.points

character argument giving the style in which points are added to the plot. See panel.densityplot for details.

layout

a method-specific default for the layout argument to the lattice functions.

xlab,ylab,main

Used to provide default axis annotations and plot labels.

cuts, at

defines number and location of values where colors change

col.regions

color palette used

lag.max

maximum lag for which autocorrelation is computed. By default, the value chosen by acf is used

prepanel,panel

suitable prepanel and panel functions for acfplot. The prepanel function omits the lag-0 auto-correlation (which is always 1) from the range calculations.

...

other arguments, passed to the lattice function. Documentation of the corresponding generics in the lattice package should be consulted for possible arguments.

subset

indices of the subset of the series to plot. The default is constructed from the start and thin arguments.

Value

• An object of class "trellis". The relevant update method can be used to update components of the object and the print method (usually called by default) will plot it on an appropriate plotting device.

See Also

Lattice for a brief introduction to lattice displays and links to further documentation.

Examples

data(line)
xyplot(line)
xyplot(line[[1]], start = 10)
densityplot(line, start = 10)
qqmath(line, start = 10)
levelplot(line[[2]])
acfplot(line, outer = TRUE)