MultiWaveAnalysis function

Generate a MultiWave analysis

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

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

Returns

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

Examples

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

See Also

• availableFilters
• availableFeatures