plotsamples | R Documentation |
This function plots the sampling paths of coefficient(s) and variance(s) stored in model term
objects typically returned from function bayesx
or read.bayesx.output
.
plotsamples(x, selected = "NA", acf = FALSE, var = FALSE,
max.acf = FALSE, subset = NULL, ...)
x |
a vector or matrix, where each column represents a different sampling path to be plotted. |
selected |
a character string containing the term name the sampling paths are plotted for. |
acf |
if set to |
var |
indicates whether coefficient or variance sampling paths are displayed and simply changes the main title. |
max.acf |
if set to |
subset |
integer. An index which selects the coefficients for which sampling paths should be plotted. |
... |
other graphical parameters to be passed to |
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.
plot.bayesx
, bayesx
, read.bayesx.output
.
## generate some data
set.seed(111)
n <- 500
## regressors
dat <- data.frame(x = runif(n, -3, 3))
## response
dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6))
## Not run:
## estimate model
b <- bayesx(y ~ sx(x), data = dat)
summary(b)
## plot sampling path for
## the variance
plot(b, term = "sx(x)", which = "var-samples")
## plot sampling paths for
## coefficients
plot(b, term = "sx(x)", which = "coef-samples")
## plot maximum autocorrelation of
## all sampled parameters of term s(x)
plot(b, term = "sx(x)", which = "coef-samples", max.acf = TRUE)
## extract samples of term sx(x)
sax <- as.matrix(samples(b, term = "sx(x)"))
## now use plotsamples
plotsamples(sax, selected = "sx(x)")
## some variations
plotsamples(sax, selected = "sx(x)", acf = TRUE)
plotsamples(sax, selected = "sx(x)", acf = TRUE, lag.max = 200)
## End(Not run)
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