predict.tempGP {DSWE} | R Documentation |
predict from temporal Gaussian process
Description
predict function for tempGP objects. This function computes the prediction f(x)
or f(x) + g(t)
depending on the temporal distance between training and test points and whether the time indices for the test points are provided.
Usage
## S3 method for class 'tempGP'
predict(object, testX, testT = NULL, trainT = NULL, ...)
Arguments
object |
An object of class tempGP. |
testX |
A matrix with each column corresponding to one input variable. |
testT |
A vector of time indices of the test points. When |
trainT |
Optional argument to override the existing trainT indices of the |
... |
additional arguments for future development |
Value
A vector of predictions at the testpoints in testX
.
Examples
data = DSWE::data1
trainindex = 1:50 #using the first 50 data points to train the model
traindata = data[trainindex,]
xCol = 2 #input variable columns
yCol = 7 #response column
trainX = as.matrix(traindata[,xCol])
trainY = as.numeric(traindata[,yCol])
tempGPObject = tempGP(trainX, trainY)
testdata = DSWE::data1[101:110,] # defining test data
testX = as.matrix(testdata[,xCol, drop = FALSE])
predF = predict(tempGPObject, testX)
[Package DSWE version 1.8.2 Index]