View source: R/zeitzeiger_cv.R
zeitzeigerPredictCv | R Documentation |
Make predictions for each observation for each fold of cross-validation.
zeitzeigerPredictCv( x, time, foldid, spcResultList, nKnots = 3, nSpc = NA, timeRange = seq(0, 1 - 0.01, 0.01), dopar = TRUE )
x |
Matrix of measurements, observations in rows and features in columns. |
time |
Vector of values of the periodic variable for observations, where 0 corresponds to the lowest possible value and 1 corresponds to the highest possible value. |
foldid |
Vector of values indicating the fold to which each observation belongs. |
spcResultList |
Output of |
nKnots |
Number of internal knots to use for the periodic smoothing spline. |
nSpc |
Vector of the number of SPCs to use for prediction. If |
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. |
dopar |
Logical indicating whether to process the folds in parallel.
Use |
A list of the same structure as zeitzeigerPredict()
, combining the
results from each fold of cross-validation.
timeDepLike |
3-D array of likelihood, with dimensions for each
observation, each element of |
mleFit |
List (for each element in |
timePred |
Matrix of predicted times for observations by values of
|
zeitzeigerPredict()
, zeitzeigerFitCv()
, zeitzeigerSpcCv()
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