rescale.variance: Noise standardisation for multivariate time series.
In InspectChangepoint: High-Dimensional Changepoint Estimation via Sparse Projection
rescale.variance R Documentation
Noise standardisation for multivariate time series.
Description
Each row of the input matrix is normalised by the estimated standard deviation computed through the median absolute deviation of increments.
Usage
rescale.variance(x)
Arguments
x
An input matrix of real values.
Details
This is an auxiliary function used by the InspectChangepoint package.
Value
A rescaled matrix of the same size is returned.
Examples
x <- matrix(rnorm(40),5,8) * (1:5)
x.rescaled <- rescale.variance(x)
x.rescaled
InspectChangepoint documentation built on May 3, 2022, 9:07 a.m.
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| rescale.variance | R Documentation |
Noise standardisation for multivariate time series.
Description
Each row of the input matrix is normalised by the estimated standard deviation computed through the median absolute deviation of increments.
Usage
rescale.variance(x)
Arguments
x |
An input matrix of real values. |
Details
This is an auxiliary function used by the InspectChangepoint package.
Value
A rescaled matrix of the same size is returned.
Examples
x <- matrix(rnorm(40),5,8) * (1:5) x.rescaled <- rescale.variance(x) x.rescaled
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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