Hello,
If you want a truncated something rng, you can use the following
function. Note that 'distr' is the name of an R distribution function
without the dpqr prefix.
rtrunc <- function(n, distr, lower = -Inf, upper = Inf, ...){
makefun <- function(prefix, FUN, ...){
txt <- paste(prefix, FUN, "(x, ...)", sep = "")
function(x, ...) eval(parse(text = txt))
}
if(length(n) > 1) n <- length(n)
pfun <- makefun("p", distr, ...)
qfun <- makefun("q", distr, ...)
lo <- pfun(lower, ...)
up <- pfun(upper, ...)
u <- runif(n, lo, up)
qfun(u, ...)
}
u <- 2; a <- 3
x <- rtrunc(1000, "norm", lower = 0, mean = u, sd = a)
hist(x)
Hope this helps,
Rui Barradas
Em 15-09-2015 16:12, (Ted Harding) escreveu:
Using non-central chi-squared (especially with df=1) is unlikely
to generate random numbers anywhere near a Normal distribution
(see below).
And "rchisq(100, df=1, ncp=u/a)" won't work anyway with u<0,
since ncp must be >= 0 (if < 0 then all are NA).
Better to shoot straight for the target (truncated Normal), though
several shots are likely to be required! For example (code which
spells it out), taking u=3 and a=2:
n <- 100
u <- 3 ; a <- 2
x <- NULL
N <- length(x)
while(N < n){
x <- c(x,rnorm(n,mean=u,sd=a))
x <- x[x>0]
N <- length(x)
}
x <- x[1:n]
Comparison with non-central chi-squared:
y <- rchisq(100, df=1, ncp=u/a)
hist(x)
hist(y)
On 15-Sep-2015 13:26:44 jlu...@ria.buffalo.edu wrote:
Your question makes no sense as stated. However, guessing at what you
want, you should perhaps consider the non-central chi-square density with
1 df and ncp = u/a, i.e,
rchisq(100, df=1, ncp=u/a)
Joe
Joseph F. Lucke, PhD
Senior Statistician
Research Institute on Addictions
University at Buffalo
State University of New York
1021 Main Street
Buffalo, NY 14203-1016
Chien-Pang Chin <chienpan...@gmail.com>
Sent by: "R-help" <r-help-boun...@r-project.org>
09/15/2015 06:58 AM
To
"r-help@r-project.org" <r-help@r-project.org>,
Subject
[R] Beta distribution approximate to Normal distribution
Hi,
I need to generate 1000 numbers from N(u, a^2), however I don't
want to include 0 and negative values. How can I use beta distribution
approximate to N(u, a^2) in R.
Thx for help
-------------------------------------------------
E-Mail: (Ted Harding) <ted.hard...@wlandres.net>
Date: 15-Sep-2015 Time: 16:12:35
This message was sent by XFMail
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