bsts (version 0.6.1)

plot.bsts.predictors: 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")