Uniform Random Distribution

Description

Generates uniformly distributed random parameter sets.

Usage

Unif(parRange, num)

Arguments

Details

In the uniform sampling, each parameter is uniformly random distributed over its range.

Value

a matrix with one row for each generated parameter set, and one column per parameter.

Note

For small sample sizes, the latin hypercube distributed parameter sets (Latinhyper) may give better coverage in parameter space than the uniform random design.

Author(s)

Karline Soetaert <karline.soetaert@nioz.nl>

See Also

Norm for (multi)normally distributed random parameter sets.

Latinhyper to generates parameter sets using latin hypercube sampling.

Grid to generate random parameter sets arranged on a regular grid

runif the R-default for generating uniformally distributed random numbers.

Examples

## 4 parameters
parRange <- data.frame(min = c(0, 1, 2, 3), max = c(10, 9, 8, 7))
rownames(parRange) <- c("par1", "par2", "par3", "par4")

## uniform
pairs(Unif(parRange, 100), main = "Uniformly random")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(FME)
Loading required package: deSolve

Attaching package: 'deSolve'

The following object is masked from 'package:graphics':

    matplot

Loading required package: rootSolve
Loading required package: coda
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FME/Unif.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Unif
> ### Title: Uniform Random Distribution
> ### Aliases: Unif
> ### Keywords: utilities
> 
> ### ** Examples
> 
> ## 4 parameters
> parRange <- data.frame(min = c(0, 1, 2, 3), max = c(10, 9, 8, 7))
> rownames(parRange) <- c("par1", "par2", "par3", "par4")
> 
> ## uniform
> pairs(Unif(parRange, 100), main = "Uniformly random")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>