Passing a function to an RTMB function

[Paul vdb]

What is the most efficient way to allow a user to pass a custom function to the likelihood?

Here is one way I have done it.

extractValue <- function(x, y){
  if(!is.null(x)) return(x)
  return(y)
}

mycars_bayeslm <- function(sd_prior = NULL, beta_priors = NULL){
  dprior_sd <- extractValue(sd_prior, function(x){dgamma(1, 1, log = TRUE)})
  dprior_beta <- extractValue(sd_prior, function(x){sum(dnorm(0, 10, log = TRUE))})
 
  parinit <- list(beta = c(0,0), sd = 5)
  negll <- function(pars){
    getAll(cars, pars)
    -sum(dnorm(dist, beta[1] + beta[2] * speed, sd, log = TRUE)) - dprior_sd(sd) - dprior_beta(beta)
  }
  obj <- MakeADFun(negll, parinit)
  return(obj)
}

obj1 <- mycars_bayeslm()
obj2 <- mycars_bayeslm(sd_prior = function(x){dnorm(x[1], 1, 10, log = TRUE)})

If I am not explicit about returning a scalar, then it does not work, which is minorly annoying.

obj3 <- mycars_bayeslm(sd_prior = function(x){dnorm(x, 1, 10, log = TRUE)})

Does anyone have a better solution? Any suggestions? Thanks so much.

[James Thorson]

Sorry that I haven't looked closely at the code, but I do something similar in `package:ecostate`, search `log_prior` argument here.

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