PredStempCens {StempCens} | R Documentation |
Prediction in spatio-temporal model with censored/missing responses
Description
This function performs spatio-temporal prediction in a set of new S
spatial locations for fixed time points.
Usage
PredStempCens(Est.StempCens, locPre, timePre, xPre)
Arguments
Est.StempCens |
an object of class |
locPre |
a matrix of coordinates for which prediction is performed. |
timePre |
the time point vector for which prediction is performed. |
xPre |
a matrix of covariates for which prediction is performed. |
Value
The function returns an object of class Pred.StempCens
which is a list given by:
predValues |
predicted values. |
VarPred |
predicted covariance matrix. |
Author(s)
Katherine L. Valeriano, Victor H. Lachos and Larissa A. Matos
See Also
Examples
set.seed(12345)
# Parameter values
beta <- c(-1,1.50)
phi <- 5
rho <- 0.60
tau2 <- 0.80
sigma2 <- 2
coord <- matrix(runif(34, 0, 10), ncol=2)
time <- matrix(1:5, ncol=1)
x <- cbind(rexp(85,2), rnorm(85,2,1))
# Data simulation
data <- rnStempCens(x, time, coord, beta, phi, rho, tau2, sigma2,
type.S="pow.exp", kappa=0.5, cens="left", pcens=0.10)
# Splitting the dataset
train <- data[11:85,]
test <- data[1:10,]
# Estimation
x <- cbind(train$x1, train$x2)
coord2 <- cbind(train$x.coord, train$y.coord)
est_teste <- EstStempCens(train$yObs, x, train$ci, train$time, coord2, train$lcl,
train$ucl, init.phi=3.5, init.rho=0.5, init.tau2=1, kappa=0.5,
type.S="pow.exp", IMatrix=FALSE, M=20, perc=0.25, MaxIter=300,
pc=0.20)
# Prediction
xPre <- cbind(test$x1, test$x2)
pre_test <- PredStempCens(est_teste, test[,1:2], test$time, xPre)
[Package StempCens version 1.2.0 Index]