Dest: Estimation Joost's Dest parameter

In dyerlab/gstudio: Tools Related to the Spatial Analysis of Genetic Marker Data

Estimation Joost's Dest parameter

Description

This function estimates the parameter (and potentially the confidence surrounding its value) for Joost's Dest.

Usage

Dest(x, stratum = "Population", nperm = 0, size.correct = FALSE)

Arguments

x	A vector of locus objects or a data.frame with locus objects.
stratum	Either a vector of strata variables if x is a locus vector or the name of the column representing strata in x if it is a data.frame.
nperm	The number of permutations to run for significance of the estimator.
size.correct	A flag indicating that the estimate should be corrected for based upon sample sizes (default=TRUE).

Value

A data.frame with Dest, Hs, Ht, and P (if asked for). When multiple loci are provided, the results also provide a multilocus estimate using the harmonic mean.

Author(s)

Rodney J. Dyer [e-mail]

Examples

 a1 <- sample( LETTERS[1:5], size=20, replace=TRUE)
 a2 <- sample( LETTERS[4:8], size=20, replace=TRUE)
 raw_alleles <- matrix( c(a1,a2), ncol=2, byrow=TRUE )
 locus <- locus( raw_alleles, type="column")
 Population <- c(rep("Pop-A",10),rep("Pop-B",10))
 Dest( locus, Population )
 a1 <- sample( LETTERS[1:5], size=20, replace=TRUE)
 a2 <- sample( LETTERS[4:8], size=20, replace=TRUE)
 raw_alleles <- matrix( c(a1,a2), ncol=2, byrow=TRUE )
 locus2 <- locus( raw_alleles, type="column")
 df <- data.frame( Population, TPI=locus, PGM=locus2 )
 Dest( df, nperm=99)

dyerlab/gstudio documentation built on Feb. 2, 2024, 8:24 p.m.