evolqg (version 0.2-2)

RarefactionStat: Non-Parametric rarefacted population samples and statistic comparison

Description

Calculates the repeatability of a statistic of the data, such as correlation or covariance matrix, via resampling with varying sample sizes, from 2 to the size of the original data.

Usage

RarefactionStat(ind.data, StatFunc, ComparisonFunc, ..., num.reps = 10,
  replace = FALSE, parallel = FALSE)

Arguments

ind.data

Matrix of residuals or indiviual measurments

StatFunc

Function for calculating the statistic

ComparisonFunc

comparison function

...

Aditional arguments passed to ComparisonFunc

num.reps

number of populations sampled per sample size

replace

If true, samples are taken with replacement

parallel

if TRUE computations are done in parallel. Some foreach backend must be registered, like doParallel or doMC.

Value

• returns the mean value of comparisons from samples to original statistic, for all sample sizes.

Details

Samples of various sizes, without replacement, are taken from the full population, a statistic calculated and compared to the full population statistic.

A specialized ploting function displays the results in publication quality.

Bootstraping may be misleading with very small sample sizes. Use with caution.

See Also

BootstrapRep

Examples

ind.data <- iris[1:50,1:4]

#Can be used to calculate any statistic via Rarefaction, not just comparisons
#Integration, for instanse:
results.R2 <- RarefactionStat(ind.data, cor, function(x, y) CalcR2(y), num.reps = 5)

#Easy access
library(reshape2)
melt(results.R2)

#Multiple threads can be used with some foreach backend library, like doMC or doParallel
#library(doParallel)
##Windows:
#cl <- makeCluster(2)
#registerDoParallel(cl)
##Mac and Linux:
#registerDoParallel(cores = 2)
#results.R2 <- RarefactionStat(ind.data, cor, function(x, y) CalcR2(y), parallel = TRUE)