Hello, I would like to optimize the function: ``` holling = function(a, b, x) { y = (a * x^2) / (b^2 + x^2) return(y) } ``` I am trying to use the function mle2 from bbmle, but how do I need to feed the data? If I give `holling` as function to be optimized, passing the starting values for `a`, `b`, and `x`, I get: ``` X = 1:60 A = 3261 B = 10 O = mle2(minuslogl = holling, start = list(a = A, h = B, x = X)) > Error in mle2(minuslogl = holling, start = list(a = A, b = B, x = X)) : some named arguments in 'start' are not arguments to the specified log-likelihood function ``` If I pass the negative log-function (assuming a binomial distribution of the data, which I am not sure about) ``` nll = function(p, n, k) { # extract parms a = p[1] h = p[2] # calculate probability of attack pred = a/(1+a*h*n) # calc NLL -sum(dbinom(k, prob = pred, size = n, log = TRUE)) } ``` then I get the same error: ``` > O = mle2(minuslogl = nll, start = list(a = A, h = B), + data = list(n = 57200000, k = A)) Error in mle2(minuslogl = nll, start = list(a = A, h = B), data = list(n = 57200000, : some named arguments in 'start' are not arguments to the specified log-likelihood function ``` but with the disadvantage of working on an assumed function (nll). How can I optimize the function `holling` properly? Thank you
-- Best regards, Luigi ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.