Predict corresponding time for groups of test observations
Source:R/zeitzeiger_group.R
zeitzeigerPredictGroup.RdPredict the value of the periodic variable for each group of test observations, where the amount of time between each observation in a group is known.
Usage
zeitzeigerPredictGroup(
xTrain,
timeTrain,
xTest,
groupTest,
spcResult,
nKnots = 3,
nSpc = NA,
timeRange = seq(0, 1 - 0.01, 0.01)
)Arguments
- xTrain
Matrix of measurements for training data, observations in rows and features in columns.
- timeTrain
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.
- xTest
Matrix of measurements for test data, observations in rows and features in columns.
- groupTest
data.frame with one row per observation in
xTest, and columns forgroupandtimeDiff. Observations in the same group should have the same value ofgroup. Within each group, the value oftimeDiffshould correspond to the amount of time between that observation and a reference time. Typically,timeDiffwill equal zero for one observation per group.- spcResult
Output of
zeitzeigerSpc().- nKnots
Number of internal knots to use for the periodic smoothing spline.
- nSpc
Vector of the number of SPCs to use for prediction. If
NA(default),nSpcwill become1:K, whereKis the number of SPCs inspcResult. Each value innSpcwill correspond to one prediction for each test observation. A value of 2 means that the prediction will be based on the first 2 SPCs.- timeRange
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.
Value
A list with the following elements, where the groups will be sorted by their names.
- timeDepLike
3-D array of likelihood, with dimensions for each group of test observations, each element of
nSpc, and each element oftimeRange.- mleFit
List (for each element in
nSpc) of lists (for each group of test observations) ofmle2objects.- timePred
Matrix of predicted times for each group of test observations by values of
nSpc.