plot_tracestack.circGLM: Plot a stack of traceplots for a circGLM object

In circglmbayes: Bayesian Analysis of a Circular GLM

Description

An alternative option to plot traceplots from circGLM objects.

Usage

plot_tracestack.circGLM(
  m,
  coef = "Beta",
  labelFormat = "default",
  ggTheme = ggplot2::theme_bw(),
  res = 10000,
  burnThinLabel = TRUE
)

Arguments

m	A circGLM object.
coef	A character string, either "Beta" or "Zeta", determining whether the continuous regression predictors are shown in reparametrized form or not.
labelFormat	A character vector, either "default", "numbered" or "latex". By default, we find the names of the variables in the circGLM object. If "numbered", the parameter names are numbered. The "latex" labels are useful if knitr is used with a Tikz device.
ggTheme	A ggplot theme object to use. The relevant theme function should be evaluated.
res	The maximum number iterations to print. If res is larger than the number of iterations in the circGLM object, a subset of size res is selected, and it is attempted to equally space the selected iterations from the full set. This is useful if there is a very large posterior sample due to having very little thinning.
burnThinLabel	Logical; if TRUE, the x-label will reflect the fact that a burn-in and a thinning factor were used. If FALSE, the x-labels will run from 1 to Q.

Value

A ggplot2 plot.

See Also

plot_trace.circGLM, plot_predict.circGLM, plot_meancompare.circGLM, plot_meanboxplot.circGLM, plot.circGLM.

Examples

plot(circGLM(th = rvmc(100, 0, 1)), type = "tracestack")

dat <- generateCircGLMData()
plot(circGLM(th ~ ., dat), type = "tracestack")

circglmbayes documentation built on Jan. 22, 2021, 5:09 p.m.