Description Usage Arguments Value Examples

Plot a summary of a POUMM fit

1 2 3 4 5 6 7 8 9 10 11 | ```
## S3 method for class '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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ```
## Not run:
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
## End(Not run)
``` |

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