selectiongain (version 2.0.40)

multistagetp: Function for calculating the truncation points

Description

This function calculates the coordinates of the truncation points Q for given selected fractions $\vec{\alpha}={ \alpha_{1},\alpha_{2},...,\alpha_{n} }$ and correlation matrix of X. The R function uniroot in core package stats is called internally to solve the truncation point equations.

Usage

multistagetp(alpha,  corr,  alg)

Arguments

alpha

is probability vector $\vec{\alpha}$ for random variable X. In plant breeding, it is also called the selected fraction.

corr

is the correlation matrix of y and X, which is introduced in the function multistagecorr. The correlation matrix must be symmetric and positive-definite. If the estimated correlation matrix is negative-definite, it must be adjusted before using this funct

alg

is used to switch between two algorithms. If alg = GenzBretz(), which is by default, the quasi-Monte Carlo algorithm from Genz et al. (2009, 2013), will be used. If alg = Miwa(), the program will use the Miwa algorithm (Mi et al.

Value

• The output is a vector of the coordinates.

Details

This function calculates the non-equi coordinate quantile vector $Q={q_{1},q_{2},...,q_{n}}$ for a multivariate normal distribution from a given $\vec{\alpha}$. It can be compared with the function qmvnorm() in R-package mvtnorm, which calculates only the equi coordinate quantile $q$ for multi-variate normal distribution from a given $\vec{\alpha}$. The function multistagetp is used by function mulistagegain to calculate the expected gain.

References

A. Genz and F. Bretz. Computation of Multivariate Normal and t Probabilities. Lecture Notes in Statistics, Vol. 195, Springer-Verlag, Heidelberg, 2009. A. Genz, F. Bretz, T. Miwa, X. Mi, F. Leisch, F. Scheipl and T. Hothorn. mvtnorm: Multivariate normal and t distributions. R package version 0.9-9995, 2013. X. Mi, T. Miwa and T. Hothorn. Implement of Miwa's analytical algorithm of multi-normal distribution. R Journal, 1:37-39, 2009.

See Also

selectiongain(), qnorm()

Examples

# first example

VCGCAandError=c(0.40,0.20,0.20,0.40,2.00)
VCSCA=c(0.20,0.10,0.10,0.20)

corr.matrix = multistagecor(maseff=0.40, VGCAandE=VCGCAandError,
VSCA=VCSCA, T=c(1,1,5), L=c(1,3,8), Rep=c(1,1,1))

N1=4500;N2=919;N3=45;Nf=10

Q=multistagetp(c(N2/N1,N3/N2,Nf/N3),  corr=corr.matrix)