growfunctions (version 0.12)

predict_plot: Plot estimated functions both at estimated and predicted time points with 95% credible intervals.

Description

Uses as input the output object from the gpdpgrow.predict() and gmrfdpgrow.predict() methods.

Usage

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)

Arguments

object

A gpdpgrow.predict or gmrfdpgrow.predict object, obtained from predict_functions(object,...).

units_label

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.

type_label

A character vector assigning a "fitted" or "predicted label for the time_points input. Defaults to type_label = c("fitted","predicted").

time_points

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".

date_label

A vector of Date values for labeling the x-axis tick marks. Defaults to 1:T .

x.axis.label

Text label for x-axis. Defaults to "time".

y.axis.label

Text label for y-axis. Defaults to "function values".

single_unit

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.

credible

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 .

Value

A list object containing the plot of estimated functions, faceted by cluster, and the associated data.frame object.

p.cluster

A ggplot2 plot object

dat.cluster

A data.frame object used to generate p.cluster.

See Also

gpdpgrow, gmrfdpgrow

Examples

## Not run: 
# library(growfunctions)
# data(cps)
# y_short             <- cps$y[,(cps$yr_label %in% c(2008:2013))]
# t_train             <- ncol(y_short)
# N                   <- nrow(y_short)
# t_test              <- 4
#  
# ## Model Runs
# 
# res_gmrf            <- gmrfdpgrow(y = y_short, 
#                                 q_order = c(2,4), 
#                                 q_type = c("tr","sn"), 
#                                 n.iter = 40, 
#                                 n.burn = 20, 
#                                 n.thin = 1) 
# 
# res_gp              <- gpdpgrow(y = y_short
#                               n.iter = 10, 
#                               n.burn = 4, 
#                               n.thin = 1, 
#                               n.tune = 0) 
# 
# ## Prediction Model Runs
# T_test             <- 4
# 
# pred_gmrf          <- predict_functions( object = res_gmrf,
#                                      J = 1000, 
#                                      T_test = T_test )
# 
# T_yshort           <- ncol(y_short)
# pred_gp            <- predict_functions( object = res_gp, 
#                      test_times = (T_yshort+1):(T_yshort+T_test) )
# 
# ## plot estimated and predicted functions
# plot_gmrf       <- predict_plot(object = pred_gmrf, 
#                                units_label = cps$st, 
#                                single_unit = TRUE, 
#                                credible = FALSE)
# 
# plot_gp         <- predict_plot(object = pred_gp, 
#                                units_label = cps$st, 
#                                single_unit = FALSE, 
#                                credible = TRUE)  
# ## End(Not run)