plot.bsts.predictors: Plot the most likely predictors

In bsts: Bayesian Structural Time Series

Plot the most likely predictors

Description

Creates a time series plot showing the most likely predictors of a time series used to fit a bsts object.

Usage

  PlotBstsPredictors(bsts.object,
                     burn = SuggestBurn(.1, bsts.object),
                     inclusion.threshold = .1,
                     ylim = NULL,
                     flip.signs = TRUE,
                     show.legend = TRUE,
                     grayscale = TRUE,
                     short.names = TRUE,
                     ...)

Arguments

bsts.object	An object of class bsts.
burn	The number of observations you wish to discard as burn-in.
inclusion.threshold	Plot predictors with marginal inclusion probabilities above this threshold.
ylim	Scale for the vertical axis.
flip.signs	If true then a predictor with a negative sign will be flipped before being plotted, to better align visually with the target series.
show.legend	Should a legend be shown indicating which predictors are plotted?
grayscale	Logical. If TRUE then lines for different predictors grow progressively lighter as their inclusion probability decreases. If FALSE then lines are drawn in black.
short.names	Logical. If TRUE then a common prefix or suffix shared by all the variables will be discarded.
...	Extra arguments to be passed to plot.

See Also

bsts PlotDynamicDistribution plot.lm.spike

Examples

  data(AirPassengers)
  y <- log(AirPassengers)
  lag.y <- c(NA, head(y, -1))
  ss <- AddLocalLinearTrend(list(), y)
  ss <- AddSeasonal(ss, y, nseasons = 12)
  ## Call bsts with na.action = na.omit to omit the leading NA in lag.y
  model <- bsts(y ~ lag.y, state.specification = ss, niter = 500,
                na.action = na.omit)
  plot(model, "predictors")

bsts documentation built on Sept. 9, 2025, 5:27 p.m.