MultiWaveAnalysis {TSEAL}

Generate a MultiWave analysis

Description

Generates a multivariate analysis by calculating a series of features from the result of applying MODWT to the input data.

Usage

MultiWaveAnalysis(
  series,
  f,
  lev = 0,
  features = c("Var", "Cor", "IQR", "PE", "DM"),
  nCores = 0
)

Arguments

series

Sample from the population (array of three dimensions [dim, length, cases]

f

Selected wavelet filter for the analysis. To see the available filters use the function availableFilters

lev

Wavelet decomposition level by default is selected using the "conservative" strategy. See chooseLevel function. Must be a positive integer (including 0 to auto-select the level)

features

It allows to select the characteristics to be calculated for the analysis. To see the available features use the function availableFeatures

nCores

Determines the number of processes that will be used in the function, by default it uses all but one of the system cores. Must be a positive integer, where 0 corresponds to the default behavior

Value

A multivariate analysis with the characteristics indicated in the parameter features. This is an object of class MultiWaveAnalysis with contains * Features: A list with the computed features * StepSelection: A selection with the most discriminant features StepDiscrim * Observations: Number of total observations * NLevels: Number of levels selected for the decomposition process * Filter: Filter used in the decomposition process

See Also

• availableFilters

• availableFeatures

Examples

load(system.file("extdata/ECGExample.rda",package = "TSEAL"))
MWA <- MultiWaveAnalysis(ECGExample,
  f = "haar", lev = 0,
  features = c("Var", "Cor"), nCores = 0
)