i having trouble using bbmle:mle2 function when trying regression. illustrate problem, have come toy example. we define minus log-likelihood poisson distribution (or custom distribution): ll <- function(beta, z, x){ -sum(stats::dpois(x, lambda = exp(z %*% beta), log = true)) } in code above, beta parameter vector estimate, z model/design matrix , x variable of interest. i generate random data work with: set.seed(2) age <- round(exp(rnorm(5000, mean = 2.37, sd = 0.78) - 1)) claim <- rpois(5000, lambda = 0.07 i can use optim regression. here intercept model: z1 <- model.matrix(claim ~ 1) optim(par = 0, fn = ll, z = z1, x = claim) here intercept + age model: z2 <- model.matrix(claim ~ age) optim(par = c(0, 0), fn = ll, z = z2, x = claim) the way large number of different models can assessed quite easy, 1 has specify model matrix. how can made work mle2 function bbmle package? i can it, if beta one-dimensional: mle2(minuslogl = functio...
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