pls (version 1.0-1)

coef.mvr: Extract Information From a Fitted PLSR or PCR Model

Description

Functions to extract the regression coefficients or the model matrix from mvr objects.

Usage

## S3 method for class 'mvr':
coef(object, comps = object$ncomp, intercept = FALSE,
     cumulative = TRUE, \dots)
## S3 method for class 'mvr':
model.matrix(object, \dots)

Value

• coef.mvr returns an array of regression coefficients. model.matrix.mvr returns the $X$ matrix.

Details

coef.mvr is used to extract the regression coefficients of a model, i.e. the $B$ in $y = XB$. An array of dimension c(nxvar, nyvar, length(comps)) is returned.

If cumulative = TRUE, coef()[,,comps[i]] are the coefficients for models with comps[i] components, for $i = 1, \ldots, length(comps)$. Also, if intercept = TRUE, the first dimension is $nxvar + 1$, with the intercept coefficients as the first row.

If cumulative = FALSE, however, coef()[,,comps[i]] are the coefficients for a model with only the component comps[i], i.e. the contribution of the component comps[i] on the regression coefficients.

model.matrix.mvr returns the (possibly coded) matrix used as $X$ in the fitting.

See Also

mvr, predict.mvr, scores

Examples

data(NIR)
mod <- pcr(y ~ X, data = NIR[NIR$train,], ncomp = 5)
B <- coef(mod, comps = 3, intercept = TRUE)
## A manual predict method:
stopifnot(drop(B[1,,] + NIR$X[!NIR$train,] %*% B[-1,,]) ==
          drop(predict(mod, comps = 3, newdata = NIR[!NIR$train,])))