| MultiSkew-package {MultiSkew} | R Documentation |
MultiSkew
Description
Computes the third multivariate cumulant of either the raw, centered or standardized data. Computes the main measures of multivariate skewness, together with their bootstrap distributions. Finally, computes the least skewed linear projections of the data
Details
Package: MultiSkew
Type: Package
Title: Measures, Tests and Removes Multivariate Skewness
Version: 1.1.1
Date: 2017-06-13
Author: Cinzia Franceschini, Nicola Loperfido
Maintainer: Cinzia Franceschini <cinziafranceschini@msn.com>
License: GPL-2
References
Bartoletti, S. and Loperfido, N. (2010). Modelling Air Pollution Data by the Skew-Normal Distribution. Stochastic Environmental Research & Risk Assessment 24, 513-517.
Loperfido, N. (2013). Skewness and the Linear Discriminant Function. Statistics & Probability Letters 83, 93-99.
Loperfido, N. (2014). Linear Transformations to Symmetry. Journal of Multivariate Analysis 129, 186-192.
Malkovich, J.F. and Afifi, A.A. (1973). On Tests for Multivariate Normality. J. Amer. Statist. Ass. 68, 176-179.
Mardia, K.V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika 57, 519-530.
Mori T.F., Rohatgi V.K. and Szekely G.J. (1993). On multivariate skewness and kurtosis. Theory Probab. Appl. 38, 547-551.
Examples
data(PM10_2006)
PM10_2006_matrix<-data.matrix(PM10_2006)
MinSkew(PM10_2006_matrix[,2:5],4)
PartialSkew(PM10_2006_matrix[,2:5])
SkewMardia(PM10_2006_matrix[,2:5])
Third(PM10_2006_matrix[,2:5], "raw")
#library(MaxSkew)
SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Directional")
SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Mardia")
SkewBoot(PM10_2006_matrix[,2:5], 50, 50, "Partial")