Numero (version 1.2.0)

nroPostprocess: Standardization using existing parameters

Description

Process a new dataset using a standardization procedure that was created for another dataset

Usage

nroPostprocess(data, mapping)

Arguments

data

A matrix or a data frame with column names.

mapping

A list object or a matrix or a data frame.

Value

A data frame of processed values.

Details

The input argument can be a data frame with the attribute "mapping" as returned from nroPreprocess() or a list object with the elements input and output that each contain a data frame or a matrix of equal size.

The function projects the input data to the values in mapping$input to determine the positions of the input values with respect to the rows in the model. These positions are then used to interpolate corresponding output values in mapping$output.

The mapping elements must have identical row and columns names.

The output data frame may have less rows and columns than the input depending on how many values were usable.

Examples

# NOT RUN {
# Import data.
fname <- system.file("extdata", "finndiane.txt", package = "Numero")
dataset <- read.delim(file = fname)

# Show original data characteristics.
print(summary(dataset))

# Preprocess a subset of data.
ds.pre <- nroPreprocess(dataset[1:100,])
print(summary(ds.pre))

# Repeat preprocessing for the whole dataset (approximation).
ds.post <- nroPostprocess(dataset, ds.pre)
print(summary(ds.post))
# }