View source: R/mixed.frequency.R
plot.bsts.mixed | 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 burn-in. |
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)
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