MaxSkewBiv: MaxSkewBiv: skewness-based projection pursuit for bivariate...

Description Usage Arguments Value Author(s) References

Description

Finds Orthogonal Data Projections with Maximal Skewness for Bivariate Random Vectors

Usage

1

Arguments

x

it is a numerical variable

y

it is a numerical variable

Value

.projectionBIV

Vector of projected data when the original data are bivariate. The user can obtain it by writing ".projectionBIV", and he can obtain a scatterplot of the projection by writing plot(.projectionBIV).

Author(s)

Cinzia Franceschini and Nicola Loperfido

References

de Lathauwer L., de Moor B.and Vandewalle J. (2000). Onthebestrank-1andrank-(R_1,R_2,...R_N) approximation of high-order tensors. SIAM Jour. Matrix Ana. Appl. 21, 1324-1342.

Loperfido, N. (2010). Canonical Transformations of Skew-Normal Variates. Test 19, 146-165.

Loperfido, N. (2013). Skewness and the Linear Discriminant Function. Statistics and Probability Letters 83, 93-99.

Malkovich, J.F. and Afifi, A.A. (1973). On Tests for Multivariate Normality. J. Amer. Statist. Ass. 68, 176-179


MaxSkew documentation built on May 2, 2019, 8:26 a.m.