predict_within_cv {plmmr}R Documentation

Predict method to use in cross-validation (within cvf)

Description

Predict method to use in cross-validation (within cvf)

Usage

predict_within_cv(
  fit,
  testX,
  type,
  fbm = FALSE,
  Sigma_11 = NULL,
  Sigma_21 = NULL
)

Arguments

fit

A list with the components returned by plmm_fit.

testX

A design matrix used for computing predicted values (i.e, the test data).

type

A character argument indicating what type of prediction should be returned. Passed from cvf(), Options are "lp," "coefficients," "vars," "nvars," and "blup." See details.

fbm

Logical: is trainX an FBM object? If so, this function expects that testX is also an FBM. The two X matrices must be stored the same way.

Sigma_11

Variance-covariance matrix of the training data. Extracted from estimated_Sigma that is generated using all observations. Required if type == 'blup'.

Sigma_21

Covariance matrix between the training and the testing data. Extracted from estimated_Sigma that is generated using all observations. Required if type == 'blup'.

Details

Define beta-hat as the coefficients estimated at the value of lambda that minimizes cross-validation error (CVE). Then options for type are as follows:

Note: the main difference between this function and the predict.plmm() method is that here in CV, the standardized testing data (std_test_X), Sigma_11, and Sigma_21 are calculated in cvf() instead of the function defined here.

Value

A numeric vector of predicted values


[Package plmmr version 4.2.1 Index]