linscale: Apply minmax linear scaling to a vector.

In nnfor: Time Series Forecasting with Neural Networks

Apply minmax linear scaling to a vector.

Description

Apply minmax linear scaling to a vector.

Usage

linscale(x, minmax = NULL, rev = c(FALSE, TRUE))

Arguments

x	Input vector.
minmax	minmax must be a list with elements "mn", "mx", "mn.orig" and "mx.orig", where "mn" and "mx" refer to the target min and max, and the remaining two refer to the current vector min and max. By default mn=-1 and mx=1. mn.orig and mx.orig can be missing, unless the scaling is reversed.
rev	Reverse scaling back to original: TRUE or FALSE.

Value

Outputs a list with elements:

• x - Scaled vector.

• minmax - List with resulting mn, mx, mn.orig and mx.orig. Can be used as input to reverse scaling.

Author(s)

Nikolaos Kourentzes, [e-mail]

Examples

  y <- rnorm(20)*100
  sc <- linscale(y)
  x <- sc$x
  print(c(min(y),max(y)))
  print(c(min(x),max(x)))
  sc.rev <- linscale(x,minmax=sc$minmax,rev=TRUE)
  print(c(min(sc.rev$x),max(sc.rev$x)))

nnfor documentation built on Nov. 15, 2023, 1:09 a.m.