Generate draws from the posterior predictive distribution
of an mbsts object.
# S3 method for mbsts
predict(object,
horizon = 1,
newdata = NULL,
timestamps = NULL,
burn = SuggestBurn(.1, object),
na.action = na.exclude,
quantiles = c(.025, .975),
seed = NULL,
...)Returns an object of class mbsts.prediction, which is a list.
An object of class mbsts.
An integer specifying the number of periods into the
future you wish to predict. If object contains a regression
component then the forecast horizon is nrow(newdata) and this
argument is not used.
A vector, matrix, or data frame containing the
predictor variables to use in making the prediction. This is only
required if object contains a regression component. If a
data frame, it must include variables with the same names as the
data used to fit object. The first observation in newdata is
assumed to be one time unit after the end of the last data used in
fitting object, and the subsequent observations are
sequential time points. If the regression part of object
contains only a single predictor then newdata can be a vector. If
newdata is passed as a matrix it is the caller's
responsibility to ensure that it contains the correct number of
columns and that the columns correspond to those in
object$coefficients.
A vector of time stamps (of the same type as the
timestamps used to fit object), with one per row of
newdata (or element of newdata, if newdata is a
vector). The time stamps give the time points as which each
prediction is desired. They must be interpretable as integer (0 or
larger) time steps following the last time stamp in object.
If NULL, then the requested predictions are interpreted as
being at 1, 2, 3, ... steps following the training data.
An integer describing the number of MCMC iterations in
object to be discarded as burn-in. If burn <= 0 then no
burn-in period will be discarded.
A function determining what should be done with
missing values in newdata.
A numeric vector of length 2 giving the lower and upper quantiles to use for the forecast interval estimate.
An integer to use as the C++ random seed. If
NULL then the C++ seed will be set using the clock.
Not used. Present to match the signature of the default predict method.
Steven L. Scott
The prediction is based off of samples taken from the posterior distribution of a multivariate Bayesian structural time series model.
As an added convenience, means and interval estimates are produced from the posterior predictive distribution.
mbsts.
predict.bsts
plot.mbsts.prediction