Package 'normalize'

Centering and scaling of numeric data

Description

Methods to normalize numeric data with respect to mean and variance.

Usage

normalize(x, center = TRUE, scale = TRUE, ...)

## Default S3 method:
normalize(x, ...)

## S3 method for class 'numeric'
normalize(x, center = TRUE, scale = TRUE, ...)

## S3 method for class 'matrix'
normalize(
  x,
  center = TRUE,
  scale = TRUE,
  byrow = FALSE,
  ignore = integer(),
  jointly = list(),
  ...
)

## S3 method for class 'data.frame'
normalize(
  x,
  center = TRUE,
  scale = TRUE,
  byrow = FALSE,
  ignore = integer(),
  jointly = list(),
  ...
)

## S3 method for class 'list'
normalize(x, center = TRUE, scale = TRUE, ...)

Arguments

x	An object to be normalized.
center	[logical(1)] Normalize to zero mean?
scale	[logical(1)] Normalize to unit variance?
...	Further arguments to be passed to or from other methods.
byrow	[logical(1)] Only relevant if x has two dimensions (rows and columns). In this case, set to TRUE to normalize row-wise or FALSE to normalize column-wise (default).
ignore	[integer()] Column indices (or row indices if byrow = TRUE) to not normalize.
jointly	[list()] Disjoint column indices (or row indices if byrow = TRUE) to normalize jointly.

Value

The normalized input x with the centering and scaling values used (if any) added as attributes "center" and "scale".

Examples

# can normalize numeric vectors, matrices, data.frames, and lists of those
normalize(
  list(
    c(-3, 0, 3),
    matrix(1:12, nrow = 3, ncol = 4),
    data.frame(a = 1:3, b = 4:6, c = 7:9, d = 10:12)
  )
)

# can ignore columns (or rows)
normalize(
  data.frame(a = 1:3, b = c("A", "B", "C"), c = 7:9, d = 10:12),
  ignore = 2
)

# can normalize columns (or rows) jointly
normalize(
  matrix(1:12, nrow = 3, ncol = 4),
  jointly = list(1:2, 3:4)
)

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