SkewBoot function

Bootstrap inference for multivariate skewness measures

Bootstrap inference for multivariate skewness measures

Computes the bootstrap distribution, its histogram and the corresponding p-value of the chosen measure of multivariate skewness (Mardia, Partial or Directional), using a given number of bootstrap replicates.

SkewBoot(data, replicates, units, type)

Arguments

  • data: data matrix
  • replicates: number of bootstrap replicates
  • units: number of rows in the data matrices sampled from the original data matrix
  • type: "Directional", "Partial" or "Mardia". If type is set equal to "Directional" or "Mardia", units is an integer greater than the number of variables. If type set equal to "Partial", units is an integer greater than the number of variables + 1

Details

The function calls the package MaxSkew 1.1, which needs to be downloaded. The number of iterations required by the package MaxSkew is set equal to 5.

Returns

  • histogram: plot of the above mentioned bootstrap distribution

  • Pvalue: p-value of the chosen skewness measure

  • Vector: vector containing the bootstrap replicates of the chosen skewness measure

Author(s)

Cinzia Franceschini and Nicola Loperfido

Examples

library(MaxSkew) data(PM10_2006) PM10_2006_matrix<-data.matrix(PM10_2006) #source("SkewBoot.R") #SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Partial") #SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Mardia") #SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Directional")
  • Maintainer: Cinzia Franceschini
  • License: GPL-2
  • Last published: 2017-06-24

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