Renvlp (version 3.4.5)

pred.eppls: Estimation or prediction for eppls

Description

Perform estimation or prediction under the Envelope-based Partial Partial Least Squares.

Usage

pred.eppls(m, X1new, X2new)

Value

The output is a list that contains following components.

value

The fitted value or the predicted value evaluated at X1new and X2new.

covMatrix.estm

The covariance matrix of the fitted value at X1new and X2new.

SE.estm

The standard error of the fitted value at X1new and X2new.

covMatrix.pred

The covariance matrix of the predicted value at X1new and X2new.

SE.pred

The standard error of the predicted value at X1new and X2new.

Arguments

m

A list containing estimators and other statistics inherited from eppls.

X1new

The value of X1 with which to estimate or predict Y. A p1 dimensional vector.

X2new

The value of X2 with which to estimate or predict Y. A p2 dimensional vector.

Details

This function evaluates the partial envelope model at new value Xnew. It can perform estimation: find the fitted value when X = Xnew, or prediction: predict Y when X = Xnew. The covariance matrix and the standard errors are also provided.

References

Park, Y., Su, Z. and Chung, D. (2022+) Envelope-based Partial Partial Least Squares with Application to Cytokine-based Biomarker Analysis for COVID-19.

Examples

  data(amitriptyline)
  
  Y <- amitriptyline[ , 1:2]
  X1 <- amitriptyline[ , 4:7]
  X2 <- amitriptyline[ , 3]
  u <- u.eppls(X1, X2, Y)
  
  u
  
  m <- eppls(X1, X2, Y, 2)
  
  pred.res <- pred.eppls(m, X1[1, ], X2[1])
  pred.res