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Calculates the posterior probability that the sample contains at least one fish from each collection and repunit

Source: R/prob_at_least_one_in_sample.R
prob_at_least_one_in_sample.Rd

This takes the output of infer_mixture() and returns two tibbles, one for collections and the other for repunits. Note that for this to work properly, infer_mixture() must have been run with a total_catch_tib, and also it is imperative that the variable_prob_is_catch parameter to infer_mixture() was at its default value of FALSE.

Usage

prob_at_least_one_in_sample(X, mix_coll, burn_in = 100)

Arguments

X

The return object from infer_mixture

mix_coll

character name of the mixture_collection within X you want to summarize the results for.

burn_in

discards the first burn_in sweeps when handling the pi_traces (for the boxplots of the pi)