Generate parameter sets from given ranges, with chosen sampling scheme
parameterSets(par.ranges, samples, method = c("sobol", "innergrid", "grid"))A named list of minimum and maximum parameter values
Number of samples to generate. For the "grid" and "innergrid"
method, may be a vector of number of samples for each parameter.
the sampling scheme; see Details
the result is a matrix, with named columns for each parameter in par.ranges.
Each row represents one parameter set.
Method "sobol" generates uniformly distributed Sobol low discrepancy numbers,
using the sobol function in the randtoolbox package.
Method "grid" generates a grid within the parameter ranges, including its extremes,
with number of points determined by samples
Method "innergrid" generates a grid within the parameter ranges, with edges
of the grid offset from the extremes. The offset is calculated as half
of the resolution of the grid diff(par.ranges)/samples/2.
delsa, which uses this function
# NOT RUN {
X.grid <- parameterSets(par.ranges=list(V1=c(1,1000),V2=c(1,4)),
samples=c(10,10),method="grid")
plot(X.grid)
X.innergrid<-parameterSets(par.ranges=list(V1=c(1,1000),V2=c(1,4)),
samples=c(10,10),method="innergrid")
points(X.innergrid,col="red")
# }
# NOT RUN {
library(randtoolbox)
X.sobol<-parameterSets(par.ranges=list(V1=c(1,1000),V2=c(1,4)),
samples=100,method="sobol")
plot(X.sobol)
# }
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