Uses as input the output object from the gpdpgrow.predict() and gmrfdpgrow.predict() methods.
predict_plot(
object = NULL,
units_label = NULL,
type_label = c("fitted", "predicted"),
time_points = NULL,
date_label = NULL,
x.axis.label = NULL,
y.axis.label = NULL,
single_unit = FALSE,
credible = TRUE
)A list object containing the plot of estimated functions, faceted by cluster,
and the associated data.frame object.
A ggplot2 plot object
A data.frame object used to generate p.cluster.
A gpdpgrow.predict or gmrfdpgrow.predict object, obtained from
predict_functions(object,...).
A vector of labels to apply to experimental units with length equal to the number of
unique units. Defaults to sequential numeric values as input with data, y.
A character vector assigning a "fitted" or "predicted
label for the time_points input. Defaults to type_label = c("fitted","predicted").
A list input of length 2 with each entry containing a numeric vector
of times - one for the observed times for the set of "fitted" functions and the other denotes
time values at which "predicted" values were rendered for the functions. This input variable
only applies to gpdpgrow objects and not gmrfdpgrow objects because the latter
covariance structure is based on adjacency for equally-spaced time points.
Defaults to 1:T_train for the list entry pointed to "fitted" and
(T_train+1):(T_train + T_test) for the list entry pointed to "predicted".
A vector of Date values for labeling the x-axis tick marks.
Defaults to 1:T .
Text label for x-axis. Defaults to "time".
Text label for y-axis. Defaults to "function values".
A scalar boolean indicating whether to plot the fitted vs data curve for
only a single experimental units (versus a random sample of 6).
Defaults to FALSE.
A scalar boolean indicating whether to plot 95 percent credible intervals for
estimated functions, bb, when plotting fitted functions versus data. Defaults to
credible = TRUE .
Terrance Savitsky tds151@gmail.com
gpdpgrow, gmrfdpgrow