Skip to contents

The log-likelihoods are calculated with a crude approximation using simulated chain summaries by linearly approximating any missing values in the empirical cumulative distribution function (ecdf).

Usage

.offspring_ll(x, offspring_dist, statistic, nsim_offspring = 100, ...)

Arguments

x

A numeric vector of chain summaries (sizes/lengths).

offspring_dist

Offspring distribution: a <function> like the ones provided by R to generate random numbers from given distributions (e.g., rpois for Poisson). More specifically, the function needs to accept at least one argument, n, which is the number of random numbers to generate. It can accept further arguments, which will be passed on to the random number generating functions. Examples that can be provided here are rpois for Poisson distributed offspring, rnbinom for negative binomial offspring, or custom functions.

statistic

The chain statistic to track as the stopping criteria for each chain being simulated when stat_threshold is not Inf; A <string>. It can be one of:

  • "size": the total number of cases produced by a chain before it goes extinct.

  • "length": the total number of generations reached by a chain before it goes extinct.

nsim_offspring

Number of simulations of the offspring distribution for approximating the distribution of the chain statistic summary (size/length)

...

any parameters to pass to simulate_chain_stats

Value

A numeric vector of log-likelihood values.

Author

Sebastian Funk James M. Azam