Use the model-estimated iGMRF precision parameters from gmrfdpgrow() to predict the iGMRF function at future time points. Inputs the gmrfdpgrow object of estimated parameters.
A companion function to
Object of class
Scalar denoting number of draws to take from posterior predictive for each unit.
The number of equally-spaced time points to predict the iGMRF functions ahead of
of the functions estimated at
further arguments passed to or from other methods.
out A list object containing containing two matrices; the first is a P x (N*T) matrix of predicted function values for each of P sampled iterations. N is slow index and denotes the number of experimental units. The second matrix is an N x T average over the P sampled draws, composed in Rao-Blackwellized fashion.
Intended as a companion function for
gmrfdpgrow for prediction
Terrance Savitsky email@example.com
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## Not run: library(growfunctions) data(cps) y_short <- cps$y[,(cps$yr_label %in% c(2010:2013))] 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 = 100, n.burn = 50, n.thin = 1) ## Prediction Model Runs T_test <- 4 pred_gmrf <- predict_functions( object = res_gmrf, J = 1000, T_test = T_test ) ## plot estimated and predicted functions plot_gmrf <- predict_plot(object = pred_gmrf, units_label = cps$st, single_unit = TRUE, credible = FALSE) ## End(Not run)
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