nscore: Transform to normal scores

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Transform each variable in a data matrix to normal scores and finding the adjustment so that mean of squares of scores is 1.

Usage

nscore(data,iopt=F)
nscoreOpta(n,mxiter=20, eps=1.e-4,iprint=F)

Arguments

data	data matrix or data frame
iopt	iopt=T to use adjustment 'a' in nscoreOpta that makes normal scores have mean of 0 and variance of 1; default is iopt=F in which case a=-0.5 is used
n	sample size
mxiter	maximum number of iterations
eps	tolerance for stopping
iprint	print flag for iterations

Value

data matrix with same number of columns as input for nscore

number near -0.5 for nscoreOpta

See Also

uscore

Examples

set.seed(123)
x=matrix(rnorm(40),20,2)
z=nscore(x)
nscoreOpta(100) # -0.5766102
nscoreOpta(1000) # -0.5522775

YafeiXu/CopulaModel documentation built on May 9, 2019, 11:07 p.m.