print.mvr {pls}

Summary and Print Methods for PLSR and PCR objects

Description

Summary and print methods for mvr and mvrVal objects.

Usage

## S3 method for class 'mvr'
print(x, ...)

## S3 method for class 'mvr'
summary(
  object,
  what = c("all", "validation", "training"),
  digits = 4,
  print.gap = 2,
  ...
)

## S3 method for class 'mvrVal'
print(x, digits = 4, print.gap = 2, ...)

## S3 method for class 'mvrVal'
as.data.frame(x, row.names = NULL, optional = FALSE, shortAlgs = TRUE, ...)

Arguments

x, object

an mvr object

...

Other arguments sent to underlying methods.

what

one of "all", "validation" or "training"

digits

integer. Minimum number of significant digits in the output. Default is 4.

print.gap

Integer. Gap between coloumns of the printed tables.

row.names

NULL or a character vector giving the row names for the data frame. Missing values are not allowed.

optional

Not used, only included to match signature of as.data.frame.

shortAlgs

Logical. Shorten algorithm names (default = TRUE).

Details

If what is "training", the explained variances are given; if it is "validation", the cross-validated RMSEPs (if available) are given; if it is "all", both are given.

Value

print.mvr and print.mvrVal return the object invisibly.

Author(s)

Ron Wehrens and Bjørn-Helge Mevik

See Also

mvr, pcr, plsr, RMSEP, MSEP

Examples

data(yarn)
nir.mvr <- mvr(density ~ NIR, ncomp = 8, validation = "LOO", data = yarn)
nir.mvr
summary(nir.mvr)
RMSEP(nir.mvr)
# Extract MVR validation statistics as data.frame:
as.data.frame(RMSEP(nir.mvr, estimate = "CV"))
as.data.frame(R2(nir.mvr))