summary.rfdata: Summary function for class rfdata

View source: R/rfdata.R

summary.rfdataR Documentation

Summary function for class rfdata

Description

This methods displays a summary containing information about the noise filtering process contained in an object of class rfdata.

Usage

## S3 method for class 'rfdata'
summary(object, ..., showid = FALSE)

Arguments

object

an object of class rfdata.

...

other options to pass to the function.

showid

a logical indicating if the indices of noisy samples must be displayed (default: FALSE).

Details

This function presents a summary containing information of the regression noise filter and the resulting dataset contained in the object of class rfdata. The information offered is as follows:

  • the function call.

  • the name of the regression noise filter.

  • the parameters associated with the noise filter.

  • the number of noisy and clean samples in the dataset.

  • the indices of the noisy and clean samples (if showid = TRUE).

Value

A list including information related to the noise filtering process contained in the object object of class rfdata with the following elements:

xclean

a data frame with the input attributes of clean samples (without errors).

yclean

a double vector with the output regressand of clean samples (without errors).

numclean

an integer with the amount of clean samples.

idclean

an integer vector with the indices of clean samples.

xnoise

a data frame with the input attributes of noisy samples (with errors).

ynoise

a double vector with the output regressand of noisy samples (with errors).

numnoise

an integer with the amount of noisy samples.

idnoise

an integer vector with the indices of noisy samples.

filter

the full name of the noise filter used.

param

a list of the argument values.

call

the function call.

This list also includes the showid argument.

See Also

print.rfdata, regEF, regDF, regHRRF, regIRF

Examples

# load the dataset
data(rock)

# apply the regression noise filter
set.seed(9)
output <- regAENN(x = rock[,-ncol(rock)], y = rock[,ncol(rock)])

# print the results
summary(output)


regfilter documentation built on Sept. 8, 2023, 6:16 p.m.