[R] pass data to log-likelihood function

[Jinsong Zhao]

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().

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---------------