R-Listers:
I am doing a quasi-maximum likelihood estimation and I get a "subscript out of bound" error message, Typically I would think this means that a subscript used in the function is literally out of bounds however I don't think this is the case. All I change in the code is a constant, that is hard-wired in (not data dependent and not parameter dependent), furthermore, the constant is not used in any subscripting.
Sorry I cannot provide a toy example, but the likelihood function looks like this:
lnL <- function(theta, gsvr, gsvR) { # theta[1]= mu, theta[2]=gamma, theta[3]=kappa1, theta[4]=kappa2
nn <- 252
d <- 0:nn
wd <- exp((theta[3] * d + theta[4] * d^2))/(sum(exp(theta[3] * d + theta[4] * d^2)))
sigsq <- numeric(length(gsvR$ret))
x <- numeric(length(gsvR$ret)
Obviously, this is not the original code you have got a problem with, since a delimeter is missing the line above. Please don't send code you have not tested yourself ....
# Below this line can be specified differently
x[1] <- 1
lenR <- length(gsvR$ret)
for (i in 1:(lenR-1)) {
x[i+1] <- sum(gsvR$rw[1:i]) + 1
rsq <- (gsvr$ret[(x[i]):(nn+x[i])])^2
sigsq[i] <- 22 * sum(wd * rsq)
}
if((nn+x[lenR]) < length(gsvr$ret)) rsq <- (gsvr$ret[(x[lenR]):(nn+x[lenR])])^2 else rsq <- NA
sigsq[length(gsvR$ret)] <- 22 * sum(wd * rsq)
sigsq <- na.omit(sigsq)
sigsq <- sigsq[-1]
# Above this line can be specified differently
Ret <- gsvR$ret[1:length(sigsq)]
mymu <- (theta[1]+theta[2]*(sigsq))
n <- length(wd)#/22 ll <- numeric(length(sigsq))
for (j in 1:length(sigsq)) {
ll[j] <- -(n/2) * log(2*pi) - (n/2) * log(sigsq[j]) - 0.5 * sum(((Ret - mymu[j])^2)/(sigsq[j]))
} l <- mean(ll)
-l
}
#########Alternative specitication################
for (i in 1:(length(gsvR$ret))) {
x[i] <- sum(gsvR$rw[1:i]) + 1
rsq <- (gsvr$ret[(x[i]):(nn+x[i])])^2
sigsq[i] <- 22 * sum(wd * rsq)
}
sigsq <- na.omit(sigsq)
###############################################
The constant that is changed is "n" when the n <- length(wd)/22 the optimization converges using both nlm and optim(with the default method), however with n <- length(wd) the functions returns the subscript out of bounds error message. Maximizing the likelihood with the alternative specification replacing the code marked in the original function allows the optimization to converge. It should be noted that the original likelihood function and the alternative specification return the same likelihood value when evaluated at the initial values.
I realize that in the original specification the variable sigsq could be all NAs and na.omit(sigsq) would produce a zero length vector, upon which sigsq[-1] would be out of bounds, however the original specification converges when n<-length(wd)/22, in which case the aforementioned case would still be true. Plus both specifications evaluate the initial values when submitted line by line (rather than in the function), using both n<-length(wd)/22 and n<-length(wd).
Could the error "subscript out of bounds" mean something different? Is there likely to be a bug?
I'm pretty sure it's a big in your code.
I haven't checked the rest of your code, since it doesn't seem to make sense to look into code that is buggy by copy&paste or whatever (see above).
There are *many* lines where your code might result in invalid subscripts, depending on the data.
Say length(gsvR$ret) == 1, then:
lenR <- length(gsvR$ret) # lenR == 1
for (i in 1:(lenR-1)) { # 1:(lenR-1) == 1:0 !!!!!
x[i+1] <- sum(gsvR$rw[1:i]) + 1 # 1:i == 1:0 !!!!!in for() you might want to use seq(along = gsvR$ret)
Uwe Ligges
I am using:
version
_ platform i386-pc-mingw32
arch i386 os mingw32 system i386, mingw32 status major 1 minor 8.0 year 2003 month 10 day 08 language R
Thanks for reading, and/or replying to this.
Jason Higbee Research Associate Federal Reserve Bank of St. Louis T: 314.444.7316 F:314.444.8731 [[alternative HTML version deleted]]
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