Predict corresponding time for groups of test observations
Source:R/zeitzeiger_group.R
zeitzeigerPredictGroup.Rd
Predict 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 forgroup
andtimeDiff
. Observations in the same group should have the same value ofgroup
. Within each group, the value oftimeDiff
should correspond to the amount of time between that observation and a reference time. Typically,timeDiff
will 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),nSpc
will become1:K
, whereK
is the number of SPCs inspcResult
. Each value innSpc
will 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) ofmle2
objects.- timePred
Matrix of predicted times for each group of test observations by values of
nSpc
.