pred.eppls | R Documentation |
Perform estimation or prediction under the Envelope-based Partial Partial Least Squares.
pred.eppls(m, X1new, X2new)
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. |
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.
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. |
Park, Y., Su, Z. and Chung, D. (2022+) Envelope-based Partial Partial Least Squares with Application to Cytokine-based Biomarker Analysis for COVID-19.
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
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