montecarlo: Random generation by Montecarlo

In agricolae: Statistical Procedures for Agricultural Research

Random generation by Montecarlo

Description

Random generation form data, use function density and parameters

Usage

montecarlo(data, k, ...)

Arguments

data	vector or object(hist, graph.freq)
k	number of simulations
...	Other parameters of the function density, only if data is vector

Value

Generate random numbers with empirical distribution.

Author(s)

Felipe de Mendiburu

See Also

density

Examples

library(agricolae)
r<-rnorm(50, 10,2)
montecarlo(r, k=100, kernel="epanechnikov")
# other example
h<-hist(r,plot=FALSE)
montecarlo(h, k=100)
# other example
breaks<-c(0, 150, 200, 250, 300)
counts<-c(10, 20, 40, 30)
op<-par(mfrow=c(1,2),cex=0.8,mar=c(2,3,0,0))
h1<-graph.freq(x=breaks,counts=counts,plot=FALSE)
r<-montecarlo(h, k=1000)
plot(h1,frequency = 3,ylim=c(0,0.008))
text(90,0.006,"Population\n100 obs.")
h2<-graph.freq(r,breaks,frequency = 3,ylim=c(0,0.008))
lines(density(r),col="blue")
text(90,0.006,"Montecarlo\n1000 obs.")
par(op)

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.