# odist: Random sampling using ovariables as parameters In OpasnetUtils: Opasnet Modelling Environment Utility Functions

## Description

Currently there are only GIS functions for producing spatial concentration maps (`GIS.Concentration.matrix`) and using (closed) spatial population data to calculate exposure (`GIS.Exposure`).

## Usage

 `1` ```odirichlet(a, n = 0, ...) ```

## Arguments

 `a` `ovariable` containing distribution parameters `n` `numeric`, number of samples. If 0, openv\$N is used instead. `...` arguments passed to `oapply`

## Details

Odirichlet is based on functions ddirichlet and rdirichlet from gtools dirichlet.R (originally contributed by Ian Wilson). The "Dirichlet function" is the multidimensional generalization of the beta distribution: it's the Bayesian canonical distribution for the parameter estimates of a multinomial distribution. Odirichlet samples from the dirichlet distribution given parameter vectors that are processed by oapply.

## Value

`ovariable`

## Author(s)

T. Rintala [email protected]

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```openv\$N <- 5 test <- Ovariable( output=data.frame( a = 1:4, b = rep(letters[1:4], each = 4), c = rep(toupper(letters[1:4]), each = 4^2), Result = 1:(4^3)), marginal=c(rep(TRUE, 3), FALSE)) out <- odirichlet(test, cols = "a") oapply(out, FUN = sum, cols = "a") test <- Ovariable( output=data.frame( a = 1:4, b = rep(letters[1:4], each = 4), Iter = rep(toupper(letters[1:4]), each = 4^2), Result = 1:(4^3)), marginal=c(rep(TRUE, 3),FALSE)) out <- odirichlet(test, cols = "a") oapply(out, FUN = sum, cols = "a") ```

OpasnetUtils documentation built on July 4, 2017, 9:44 a.m.