predict.RFPCA: Obtains the predicted value for a set of new sparse...

In CrossD/RFPCA: Sparse and Dense Riemannian FPCA

Obtains the predicted value for a set of new sparse observations

Description

Obtains the predicted value for a set of new sparse observations

Usage

## S3 method for class 'RFPCA'
predict(
  object,
  newLy,
  newLt,
  sigma2 = NULL,
  K,
  xiMethod = c("CE", "IN"),
  type = c("xi", "traj"),
  ...
)

Arguments

object	An 'RFPCA' object
newLy	A list containing the new response values; each entry corresponds to a subject and should be a matrix in which each column is an observation.
newLt	A list containing the new time points; each entry corresponds to a subject and should be a vector.
sigma2	The noise variance to use for the prediction. Serves as a regularization parameter. If left as 'NULL', use the one chosen when fitting 'object'.
K	The number of components to apply. If missing, default to all components in 'object'
xiMethod	Either to use the conditional expectation (''CE'‘) or the integration method ('’IN'') to predict
type	Either to predict the FPC scores (''xi'‘) or the underlying trajectories ('’traj'')
...	Not used

Value

A 2D array of predicted scores with entries corresponds to (i, k)

CrossD/RFPCA documentation built on Aug. 24, 2023, 4:42 p.m.