Plot a summary of a POUMM fit
# S3 method for summary.POUMM plot( x, type = c("MCMC"), doPlot = TRUE, stat = c("alpha", "theta", "sigma", "sigmae", "g0", "H2tMean"), chain = NULL, doZoomIn = FALSE, zoomInFilter = paste0("(stat %in% c('H2e','H2tMean','H2tInf','H2tMax') & ", "(value >= 0 & value <= 1) ) |", "( !stat %in% c('H2e','H2tMean','H2tInf','H2tMax') & ", "(value <= median(HPDUpper) + 4 * (median(HPDUpper) - median(HPDLower)) &", "value >= median(HPDLower) - 4 * (median(HPDUpper) - median(HPDLower))))"), palette = c("#999999", "#0072B2", "#CC79A7", "#E69F00", "#D55E00", "#56B4E9", "#009E73", "#F0E442"), prettyNames = TRUE, ... )
| x | An object of class POUMM. |
|---|---|
| type | A character indicating the type of plot(s) to be generated. Defaults to "MCMC", resulting in a trace and density plot for the selected statistics (see argument stat). Currently, only 'MCMC' type is supported. |
| doPlot | Logical indicating whether a plot should be printed on the currently active graphics device or whether only to return a list of plot- objects for further processing. Defaults to TRUE. |
| stat | A character vector with the names of statistics to be plotted. These should be names from the stats-list (see argument statFunctions). Defaults to c("alpha", "theta", "sigma", "sigmae", "H2tMean", "H2tInf"). |
| chain | A vector of integers indicating the chains to be plotted. |
| doZoomIn | (type MCMC only) A logical value indicating whether the produced plots should have a limitation on the x-axis according to an expression set in zoomInFilter (see below). Default value is FALSE. |
| zoomInFilter | A character string which evaluates as logical value. If doZoomIn is set to TRUE, this filter is applied to each point in each MCMC chain and the data-point is filtered out if it evaluates to FALSE. This allows to zoomIn the x-axis of density plots but should be used with caution, since filtering out points from the MCMC-sample can affect the kernel densities. Unfortunately, filtering out values is currently the only way to affect the limits of individual facets in ggplot2. The default value is a complicated expression involving the HPD from all MCMC chains (normally one chain from the prior and 2 chains from the posterior): zoomInFilter = paste0("stat The identifiers in this expression can be any column names found in a summary of a POUMM object. |
| palette | A vector of colors (can be character strings) corresponding to the different chains (in their order 1 (prior), 2, 3). Defaults to c("#999999", "#0072B2", "#CC79A7", "#E69F00", "#D55E00", "#56B4E9", "#009E73", "#F0E442"), which is a color-blind friendly. |
| prettyNames | A logical indicating if greek letters and sub/superscripts should be used for the names of columns in the posterior density pairs-plot. |
| ... | Not used; included for compatibility with the generic function plot. |
If doPlot==TRUE, the function returns nothing and produces output on the current graphics device as a side-effect. Otherwise, the function returns a list of plot-objects: traceplot and densplot.
if (FALSE) { library(POUMM) set.seed(1) N <- 1000 # create a random non-ultrametric tree of N tips tree <- ape::rtree(N) # Simulate the evolution of a trait along the tree z <- rVNodesGivenTreePOUMM( tree, g0 = 8, alpha = 1, theta = 4, sigma = 1.2, sigmae = .8) fit <- POUMM(z[1:N], tree, spec = list(nSamplesMCMC = 4e5)) # Summarize the results from the fit in a table: summary(fit) # Create plots for some of the inferred parameters/statistics: pl <- plot(fit, stat = c("alpha", "theta", "sigma", "sigmae", "H2tMean"), doZoomIn = TRUE, zoomInFilter = paste("!(stat %in% c('alpha', 'sigma', 'sigmae')) |", "(value >= 0 & value <= 8)"), doPlot = FALSE) pl$traceplot pl$densplot }