stLMM-methods: Print, summarize, and plot stLMM objects

In stLMM: Bayesian Spatial and Space-Time Linear Mixed Models

Print, summarize, and plot stLMM objects

Description

S3 methods for compact inspection of fitted, recovered, and prediction objects. Summaries report posterior means, standard deviations, and quantiles for active sample blocks only. Plot methods use base graphics and choose conservative defaults to avoid drawing very large posterior or prediction objects by accident.

Usage

## S3 method for class 'stLMM'
print(x, ...)
## S3 method for class 'stLMM'
summary(object, probs = c(0.025, 0.5, 0.975),
  burn = 0L, parameters = NULL, ...)
## S3 method for class 'stLMM'
plot(x, type = c("trace", "density"), parameters = NULL,
  max_parameters = 12L, burnin = 0L, thin = 1L, ...)
## S3 method for class 'stLMM_chains'
print(x, ...)
## S3 method for class 'stLMM_chains'
summary(object, probs = c(0.025, 0.5, 0.975),
  diagnostics = TRUE, include_w = FALSE, burn = 0L,
  parameters = NULL, ...)
## S3 method for class 'stLMM_chains'
plot(x, type = c("trace", "density"),
  parameters = NULL, max_parameters = 12L, include_w = FALSE,
  n_col = NULL, chain_colors = NULL, lwd = 1, burnin = 0L,
  thin = 1L, ...)
## S3 method for class 'stLMM_recovery'
print(x, ...)
## S3 method for class 'stLMM_recovery'
summary(object, probs = c(0.025, 0.5, 0.975),
  burn = 0L, parameters = NULL, include_w = FALSE, max_w = 20L, ...)
## S3 method for class 'stLMM_recovery_chains'
summary(object,
  probs = c(0.025, 0.5, 0.975), diagnostics = TRUE,
  include_w = FALSE, burn = 0L, parameters = NULL, ...)
## S3 method for class 'stLMM_recovery'
plot(x, term = NULL, nodes = NULL,
  type = c("trace", "density", "fitted"), observed = NULL,
  max_nodes = 12L, burnin = 0L, thin = 1L, ...)
## S3 method for class 'stLMM_recovery_chains'
plot(x, type = c("trace", "density"),
  parameters = NULL, max_parameters = 12L, include_w = FALSE, ...)
## S3 method for class 'stLMM_prediction'
print(x, ...)
## S3 method for class 'stLMM_prediction'
summary(object, probs = c(0.025, 0.5, 0.975),
  include_y = !is.null(object$y_samples), ...)
## S3 method for class 'stLMM_prediction'
plot(x, sample = c("mu", "y"),
  type = c("interval", "density", "scatter"), rows = NULL,
  observed = NULL, probs = c(0.025, 0.5, 0.975), max_rows = 200L,
  burnin = 0L, thin = 1L, ...)
## S3 method for class 'stLMM_prediction_chains'
plot(x, sample = c("mu", "y"),
  type = c("interval", "density"), rows = NULL,
  probs = c(0.025, 0.5, 0.975), max_rows = 200L,
  burnin = 0L, thin = 1L, ...)

Arguments

x, object	An stLMM, stLMM_recovery, or stLMM_prediction object, or the corresponding multi-chain object.
probs	Posterior quantiles to report. Prediction interval plots expect three probabilities: lower, center, and upper.
type	Plot type. For fit objects, "trace" or "density". For recovery objects, "trace", "density", or "fitted". For prediction objects, "interval", "density", or "scatter".
parameters	Optional exact parameter names to summarize or plot for an stLMM fit. For summaries, unlisted parameters are omitted from the returned parameter table or tables.
max_parameters	Maximum number of parameters to plot by default.
burn	Number of initial posterior draws to discard before computing fit summaries and multi-chain diagnostics. The default 0L uses all retained draws. This affects only the summary call; it does not modify the stored posterior samples.
diagnostics	Logical; for multi-chain summaries, compute coda diagnostics such as potential scale reduction and effective sample size.
burnin	Number of initial plotted draws to discard. This affects only the plotting call; it does not modify the stored posterior samples.
thin	Keep every thin-th plotted draw after burnin. This affects only the plotting call.
include_w	Logical; include summaries of saved or recovered latent process samples. Defaults to FALSE because these can be large.
n_col	Optional number of columns for multi-chain fit trace or density plot panels. Defaults to a compact base graphics layout.
chain_colors	Optional vector of colors for multi-chain fit plots. Values are recycled to the number of chains.
lwd	Line width for multi-chain fit trace or density plots.
max_w	Maximum number of latent process nodes summarized when include_w = TRUE.
term	Recovered process term to plot. Defaults to the first recovered term.
nodes	Latent process nodes to plot.
max_nodes	Maximum number of recovered nodes to plot by default.
include_y	Logical; include posterior predictive observation summaries when y_samples were simulated.
sample	Prediction sample matrix to plot: "mu" or "y".
rows	Prediction rows to plot.
observed	Observed values for recovery fitted-value scatter plots or prediction scatter plots. Recovery plots use the fitted response by default.
max_rows	Maximum number of prediction rows plotted by default.
...	Additional arguments passed to base plotting functions.

Value

Print methods return x invisibly. Summary methods return summary objects. Plot methods return x invisibly.

stLMM documentation built on Nov. 12, 2026, 1:07 a.m.