# dists.product.pair: Distribution of product of several discrete random variables... In DNAprofiles: DNA Profiling Evidence Analysis

## Description

Distribution of product of several discrete random variables as product X*Y

## Usage

 ```1 2``` ```dists.product.pair(dists, n.max = 1e+06, appr = FALSE, appr.method = 1L, n.max.appr = 1000, r0 = 0.01, R = 1.05) ```

## Arguments

 `dists` a list of distributions `n.max` maximum number of mass points of discrete distribution used in the process `appr` if TRUE, then the distributions are shrunken (approximated), if necessary, to not exceed n.max `appr.method` integer: 1 (merge mass points to lower bound); 2 (merge to upper bound) `n.max.appr` maximum number of mass points of shrunken distributions `r0` numeric, relative tolerance used in first step of shrinking the distributions `R` numeric, `r0` is multiplied with `R` until the number of mass points is at most `n.max.appr`

## Value

list with named sublists:

• cumdist1: a list with vectors `x`, `Fx`

• dist2: a list with vectors `x`, `fx`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```data(freqsNLngm) set.seed(123) x <- sample.profiles(1,freqsNLngm) # per locus distribution of kinship index dists <- ki.dist(x,hyp.1="FS",hyp.2="UN",hyp.true="UN") n <- sapply(dists,function(x) length(x\$fx)) prod(n) # too many outcomes to store! # but, for two subsets of the loci, the distribution can be obtained pair <- dists.product.pair(dists) str(pair) # with these, we can compute exceedance probabilities quickly # obtain the cdf as a function cdf <- dist.pair.cdf(pair) cdf(1) # plot the cdf x0 <- seq(from=-10,to=5,length=50) plot(x0,cdf(10^x0),type="l",xlab="x",ylab="Fn(x)") ```

DNAprofiles documentation built on Jan. 15, 2017, 9:27 p.m.