On 9/4/2008 10:54 AM, Jinsong Zhao wrote:
Hi there,
When I do bootstrap on a maximum likelihood estimation, I try the
following code, however, I get error:
Error in minuslogl(alpha = 0, beta = 0) : object "x" not found
It seems that mle() only get data from workspace, other than the
boot.fun().
This is the way R does scoping. Your ll function was defined in the
global environment, so that's where it will look for x, n and r. If you
want it to look at the local variables in boot.fun, then you should
define it in boot.fun.
Duncan Murdoch
My question is how to pass the data to mle() in my case.
I really appreciated to any suggestions.
Best wishes,
Jinsong
#-----------code start here---------------
x <- c(32, 16, 8, 4, 2, 1)
r <- c(20, 12, 10, 8, 6, 0)
n <- c(20, 20, 20, 20, 20, 20)
mydata <- data.frame(x = x, r = r, n = n)
rm(x, r, n) #if not rmed, it will affect the final result.
ll <- function(alpha, beta) { #how to pass the data to this function?
x <- log10(x)
P <- pnorm(alpha + beta * x)
P <- pmax(pmin(P,1),0)
-(sum(r * log(P)) + sum((n - r)* log(1-P)))
}
boot.fun <- function(data, index) {
boot.data <- data[index, ]
# it seems that the following three line dose nothing with the mle()
x <- boot.data$x
r <- boot.data$r
n <- boot.data$n
fit <- mle(ll, start = list(alpha = 0, beta = 0), method = "BFGS")
boot.coef <- coef(fit)
stats <- -boot.coef[1] / boot.coef[2]
}
library(stats4)
library(boot)
myboot <- boot(mydata, boot.fun, R = 199)
# give the error message:
# Error in minuslogl(alpha = 0, beta = 0) : object "x" not found
#-----------code end here---------------
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and provide commented, minimal, self-contained, reproducible code.
