plot.bsts.mixed {bsts}  R Documentation 
Functions for plotting the output of a mixed frequency time series regression.
## S3 method for class 'bsts.mixed' plot(x, y = c("state", "components", "coefficients", "predictors", "size"), ...) PlotBstsMixedState(bsts.mixed.object, burn = SuggestBurn(.1, bsts.mixed.object), time = NULL, fine.scale = FALSE, style = c("dynamic", "boxplot"), trim.left = NULL, trim.right = NULL, ...) PlotBstsMixedComponents(bsts.mixed.object, burn = SuggestBurn(.1, bsts.mixed.object), time = NULL, same.scale = TRUE, fine.scale = FALSE, style = c("dynamic", "boxplot"), layout = c("square", "horizontal", "vertical"), ylim = NULL, trim.left = NULL, trim.right = NULL, ...)
x 
An object of class 
bsts.mixed.object 
An object of class 
y 
A character string indicating the aspect of the model that should be plotted. 
burn 
The number of MCMC iterations to discard as burnin. 
time 
An optional vector of values to plot against. If missing, the default is to obtain the time scale from the original time series. 
fine.scale 
Logical. If 
same.scale 
Logical. If 
style 
character. If "dynamic" then a dynamic distribution plot will be shown. If "box" then boxplots will be shown. 
layout 
A character string indicating whether the plots showing components of state should be laid out in a square, horizontally, or vertically. 
trim.left 
A logical indicating whether the first (presumedly partial) observation in the aggregated state time series should be removed. 
trim.right 
A logical indicating whether the last (presumedly partial) observation in the aggregated state time series should be removed. 
ylim 
Limits for the vertical axis. Optional. 
... 
Additional arguments to be passed to

PlotBstsMixedState
plots the aggregate state
contribution (including regression effects) to the mean, while
PlotBstsComponents
plots the contribution of each state
component separately. PlotBstsCoefficients
creates a
significance plot for the predictors used in the state space
regression model.
These functions are called for their side effect, which is to produce a plot on the current graphics device.
bsts.mixed
PlotDynamicDistribution
plot.lm.spike
PlotBstsSize
## Not run: ## This example is flaky and needs to be fixed data < SimulateFakeMixedFrequencyData(nweeks = 104, xdim = 20) state.specification < AddLocalLinearTrend(list(), data$coarse.target) weeks < index(data$predictor) months < index(data$coarse.target) which.month < MatchWeekToMonth(weeks, months[1]) membership.fraction < GetFractionOfDaysInInitialMonth(weeks) contains.end < WeekEndsMonth(weeks) model < bsts.mixed(target.series = data$coarse.target, predictors = data$predictors, membership.fraction = membership.fraction, contains.end = contains.end, which.coarse = which.month, state.specification = state.specification, niter = 500) plot(model, "state") plot(model, "components") ## End(Not run)