n Realizations of a Stochastic Process assigned to dynamically generated variable names?
You can do things like this without explicit loops and if you store the individual realizations in a list or matrix then it is a lot cleaner than creating multiple objects. Here is some example code to try:
tsnfun <- function(n, init=10, mean=0, sd=1){
x <- numeric(n)
x[1] <- init
x[-1] <- rnorm(n-1, mean, sd)
cumsum(x)
}
tsnmat <- replicate( 10, tsnfun( 250, mean=0.01, sd=0.025) )
tsnlist <- lapply( c(50, 100, 150, 200, 250), tsnfun, mean=0.01, sd=0.025 )
matplot(1:250, tsnmat, type='l', lwd=2, col='maroon')
colMeans(tsnmat)
apply(tsnmat, 2, acf)
op <- par(ask=TRUE)
lapply( tsnlist, function(x) plot.ts(x, lwd=2, col='maroon') )
par(op)
sapply( tsnlist, mean )
sapply( tsnlist, '[', 1:2 )
acf(tsnlist[[2]])
Hope this helps,
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On Behalf Of Vishal Belsare [shoot.spam at gmail.com]
Sent: Sunday, May 25, 2008 1:02 PM
To: r-help at r-project.org
Subject: [R] n Realizations of a Stochastic Process assigned to dynamically generated variable names?
Sent: Sunday, May 25, 2008 1:02 PM
To: r-help at r-project.org
Subject: [R] n Realizations of a Stochastic Process assigned to dynamically generated variable names?
I am interested in creating multiple (say 1000) time series, from a
given stochastic process, of length 250. I want to refer to each
realization with its own variable name, of the format say, tsn, where
n is the n'th simulation. i.e. ts1, ts2, ts3, ts4, .... , ts1000
The way I am thinking of doing this is placing the following code
within another loop, and the 'tsn' assignment should happen as ts1 and
so on, the n being taken from the iteration of the outer loop.
However, crucially, I don't know how/whether I can create variable
names dynamically and assign values to them.
#begin
tsn <- (10);
for (i in 1:250) {
tsn <- c(tsn, tsn[i] + rnorm(1, mean=0.01, sd=0.025))
};
plot.ts(tsn, lwd=2, col="maroon");
#end
Thanks in anticipation.
Best Regards
Vishal Belsare
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