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. Not yet available in S-PLUS.
## S3 method for class 'mcmc':
densityplot(x, data,
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, data,
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, data, 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, data,
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, data,
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, data,
outer, layout = c(1, nvar(x)),
default.scales = list(y = list(relation = "free")),
type = 'l',
start = 1, thin = 1,
xlab = "Iteration number",
ylab = "",
main = attr(x, "title"),
...,
subset)
## S3 method for class 'mcmc.list':
xyplot(x, data, outer = FALSE, groups = !outer,
aspect = "xy", layout = c(1, nvar(x)),
default.scales = list(y = list(relation = "free")),
type = 'l',
start = 1, thin = 1,
xlab = "Iteration number",
ylab = "",
main = attr(x, "title"),
...,
subset)
acfplot(x, data, ...)
## S3 method for class 'mcmc':
acfplot(x, data, 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, data, 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)
"mcmc"
or "mcmc.list"
object."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,"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 resxyplot
for details. The default for
these methods is chosen carefully - check what the default plot
looks like before changingscales
parameter for the method. It is unlikely
that a user will wish to change this parameter. Pass a value for
scales
(see
panel.xyplot
for possiblpanel.densityplot
for
details.layout
argument
to the lattice functions.acf
is usedacfplot
. The prepanel function omits the lag-0
auto-correlation (which is always 1) from the range calculations.lattice
package should be consulted for possible arguments.start
and thin
arguments.Lattice
for a brief introduction to
lattice displays and links to further documentation.data(line)
xyplot(line)
xyplot(line[[1]], start = 10)
densityplot(line, start = 10)
qqmath(line, start = 10)
levelplot(line[[2]])
acfplot(line, outer = TRUE)
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