MCdesign: Monte Carlo sampling for metrology applications
In ATmet: Advanced Tools for Metrology

Description Usage Arguments Details Value Author(s) Examples

View source: R/MCdesign.R

Creates Monte Carlo sampling designs for metrology applications

1	MCdesign(N,k,distrib,distrib.pars,x)

`N`	The number of design points.
`k`	The number of the input variables of the numerical code.
`distrib`	A named list of length `k` of names of distribution functions associated with the input variables of the code. See Details for defaults.
`distrib.pars`	A named list of lists of parameters describing the distributions associated with `distrib`. If `distrib` is present but `distrib.pars` is not the function uses the standardized versions of the distributions, see Details.
`x`	A named list containing the names of the input variables of the numerical code. See Details for defaults.

This function creates a sampling design based on a Monte Carlo simulation.

If distrib or members of it are missing, an error message is displayed. Distributions have to be chosen among uniform(unif), triangular(triang), normal(norm), truncated normal(tnorm), student(t), location-scale student(t.scaled).

If distrib.pars is missing or misspecified, the standardized parameters of the associated distributions in distrib are used for all the variables in x:

unif : min=0, max=1

triang : min=0, max=1, mode=0.5

norm : mean=0, sd=1

tnorm : mean=0, sd=1, lower=0, upper=+Inf

t : nu=100

t.scaled : nu=100, mean=0, sd=1

If x or members of it are missing, arbitrary names of the form 'Xn' are applied to the columns of the output table. Names are automatically abbreviated to 15 characters.

A table containing the MC design with margins in distrib.

Severine Demeyer severine.demeyer@lne.fr

  
  N<- 100
  k<- 4
  x<- list("X1","X2","X3","X4")
  distrib<- list("norm","norm","unif","t.scaled")
  distrib.pars<- list(list(0,2),list(0,1),list(20,150),list(2,0,1))
  MCdesign(N,k,distrib,distrib.pars,x)