BASiCS_DiagPlot {BASiCS} | R Documentation |
Plot parameter values and effective sample size. See effectiveSize for more details on this diagnostic measure.
BASiCS_DiagPlot( object, Parameter = "mu", Measure = c("ess", "geweke.diag"), x = NULL, y = NULL, LogX = isTRUE(x %in% c("mu", "delta")), LogY = isTRUE(y %in% c("mu", "delta")), Smooth = TRUE, na.rm = TRUE ) BASiCS_diagPlot(...)
object |
an object of class |
Parameter |
Optional name of a chain parameter to restrict the histogram;
if not supplied, all parameters will be assessed.
Possible values: |
Measure |
Character scalar specifying the diagnostic measure to plot. Current options are effective sample size and the Geweke diagnostic criterion. |
x, y |
Optional MCMC parameter values to be plotted on the x or y axis, respectively. If neither is supplied, Parameter will be plotted on the x axis and effective sample size will be plotted on the y axis as a density plot. |
LogX, LogY |
A logical value indicating whether to use a log10 transformation for the x or y axis, respectively. |
Smooth |
A logical value indicating whether to use smoothing
(specifically hexagonal binning using |
na.rm |
Logical value indicating whether NA values should be removed before calculating effective sample size. |
... |
Unused. |
A ggplot object.
Alan O'Callaghan
# Built-in example chain data(ChainSC) # Point estimates versus effective sample size BASiCS_DiagPlot(ChainSC, Parameter = "mu") # Effective sample size as colour, mu as x, delta as y. BASiCS_DiagPlot(ChainSC, x = "mu", y = "delta")