forecast, foreach, dplyr, forcats, ggplot2, utils, stats,
tibble

Estimate the Population Size for the Mb Capture-Recapture Model
Applies an objective Bayesian method to the Mb capture-recapture model to estimate the population size N.  The Mb model is a class of capture-recapture methods used to account for variations in capture probability due to animal behavior.  Under the Mb formulation,  the initial capture of an animal may effect the probability of subsequent captures due to their becoming "trap happy" or "trap shy."

c(
person("Andrea", "Riboldi", email = "andreariboldi.ar@gmail.com", role = c("aut", "cre")),
person("Ivan Luciano", "Danesi", email = "ivanluciano.danesi@unicredit.eu", role = c("aut")),
person("Fabio", "Piacenza", email = "fabio.piacenza@unicredit.eu", role = c("aut")),
person("Ruben", "Ciaponi", role = c("ctb")),
person("Stephen", "Allen", role = c("ctb")),
person("Novella", "Saccenti", role = c("ctb")),
person("Annarita", "Filippi", role = c("ctb")))
Andrea Riboldi [aut, cre],
Ivan Luciano Danesi [aut],
Fabio Piacenza [aut],
Ruben Ciaponi [ctb],
Stephen Allen [ctb],
Novella Saccenti [ctb],
Annarita Filippi [ctb]
An implementation for computing Optimal B-Robust Estimators (OBRE) of two
parameters distributions. The procedure is composed by some equations
that are evaluated alternatively until the solution is reached. Some tools
for analyzing the estimates are included. The most relevant is OBRE
covariance matrix computation using a closed formula.

Objective Bayesian Model Discrimination in Follow-Up Designs
Marta Nai Ruscone based on Laura Deldossi's code.
Implements the objective Bayesian methodology proposed in Consonni and Deldossi in order to choose the optimal experiment that better discriminate between competing models.

Laura Deldossi and Marta Nai Ruscone based on Daniel Meyer's code (2016)
Implements the objective Bayesian methodology proposed in Consonni and Deldossi in order to choose the optimal experiment that better discriminate between competing models. G.Consonni, L. Deldossi (2014) Objective Bayesian Model Discrimination in Follow-up Experimental Designs, Test. <DOI:10.1007/s11749-015-0461-3>.