Fasymp: Asymptotical distribution of the maximally selected...
In SNPmaxsel: Maximally selected statistics for SNP data

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/Fasymp.r

This function computes the asymptotical distribution of the maximally selected chi-square statistic, where maximal selection is performed over the test statistics defined by type or user-defined through groups.

1	Fasymp(t,a.vec,type=NULL,groups=NULL)

`t`	the value at which the distribution function has to be computed.
`a.vec`	A vector of length K giving the proportion of observations in each category. Its sum must be 1. If `type`="inter.ord" or "inter.cat", `a.vec` must have length 9.
`type`	must be one of "ordinal", "all.pairs", "all.partitions", "inter.ord", "inter.cat", "inter.ord.main". If `type`=`NULL`, the chi-square statistics are computed for the groups defined by `groups`
`groups`	If `type`=`NULL`, the chi-square statistics are computed for the groups defined by `groups`. `groups` must be a list with m elements, where m is the number of considered chi-square statistics. Each element is a list with two elements `group1` and `group2`. `groups$group1` and `groups$group2` are numeric vectors giving the indices of the categories included in both groups. See example below.

This function uses the function pmvnorm from the package mvtnorm. If the considered test statistics are defined by groups, groups should not have more than 100 elements, since the pmvnorm function becomes unstable (or computationally prohibitive) for such a high dimension.

the value of the distribution function at t.

Anne-Laure Boulesteix (http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/index.html)

Boulesteix AL, Strobl C, Weidinger S, Wichmann HE, Wagenpfeil S, 2007. Multiple testing for SNP-SNP interactions. Statistical Applications in Genetics and Molecular Biology 6:37.

maxsel.asymp.test, maxsel.

# load SNPmaxsel library
# library(SNPmaxsel)

Fasymp(t=2,a.vec=c(0.2,0.1,0.05,0.05,0.6),type="ord")
Fasymp(t=2,a.vec=c(0.2,0.1,0.05,0.05,0.6),type="all.pairs")
Fasymp(t=2,a.vec=c(0.2,0.1,0.05,0.05,0.6),type="all.partitions")

Fasymp(t=2,a.vec=c(0.2,0.1,0.1,0.1,0.05,0.05,0.05,0.05,0.3),type="inter.ord")
Fasymp(t=2,a.vec=c(0.2,0.1,0.1,0.1,0.05,0.05,0.05,0.05,0.3),type="inter.cat")

# Creating a user-defined groups list 
# (correponding to type)="ord" with K=5)
my.groups<-list(list(group1=1,group2=2:5),list(group1=1:2,group2=3:5),
list(group1=1:3,group2=4:5),list(group1=1:4,group2=5))

Fasymp(t=2,a.vec=c(0.2,0.1,0.05,0.05,0.6),type=NULL,groups=my.groups)