Predict corresponding time for test observationsSource:
Predict the value of the periodic variable for test observations given training data and SPCs.
zeitzeigerPredict( xTrain, timeTrain, xTest, spcResult, nKnots = 3, nSpc = NA, timeRange = seq(0, 1 - 0.01, 0.01) )
Matrix of measurements for training data, observations in rows and features in columns.
Vector of values of the periodic variable for training observations, where 0 corresponds to the lowest possible value and 1 corresponds to the highest possible value.
Matrix of measurements for test data, observations in rows and features in columns.
Number of internal knots to use for the periodic smoothing spline.
Vector of the number of SPCs to use for prediction. If
Kis the number of SPCs in
spcResult. Each value in
nSpcwill correspond to one prediction for each test observation. A value of 2 means that the prediction will be based on the first 2 SPCs.
Vector of values of the periodic variable at which to calculate likelihood. The time with the highest likelihood is used as the initial value for the MLE optimizer.
3-D array of likelihood, with dimensions for each test observation, each element of
nSpc, and each element of
List (for each element in
nSpc) of lists (for each test observation) of
Matrix of predicted times for test observations by values of