cscale: Functions scale real and imaginary parts of a complex...

In config-i1/complex: Time Series Analysis and Forecasting Using Complex Variables

Functions scale real and imaginary parts of a complex variable

Description

Function cscale() will do the scaling based on the selected method, while the function cdescale() will transform the variable to get to the original units.

Usage

cscale(y, scaling = c("normalisation", "standardisation", "max"))

cdescale(yScaled, y, scaling = c("normalisation", "standardisation", "max"))

Arguments

y	vector of a complex variable in the original scale.
scaling	scaling method to use. "normalisation" implies scaling to make sure that y lie in [0, 1] (subtract the minimum value and divide by the range). "standardisation" standardises the variable (i.e. subtract the mean then divide by standard deviation). "max" just divides the variable by the maximum value.
yScaled	vector of the already scaled complex variable.

Value

A vector of the same size as y, containing scaled complex variable.

Author(s)

Ivan Svetunkov, [e-mail]

References

• Svetunkov, S. & Svetunkov I. (2022) Complex Autoregressions. In Press.

See Also

scale

Examples

# Generate random complex variables
y <- complex(real=rnorm(100,10,10), imaginary=rnorm(100,10,10))

yScaled <- cscale(y)
cdescale(yScaled, y)

config-i1/complex documentation built on Oct. 9, 2024, 3:04 p.m.