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Introduction

This project aims at delivering a very easy approach to Bayesian modelling in Ecology. To do so, I used several books as Bayesian Methods for Ecology by Michael A. McCarthy. In page 3 of the book, there is the general scheme to have in mind:

Data and codes are available here

prior + data $\xrightarrow{\text{model}}$ posterior

The other important thing is the expression based on Bayes theorem:

[ P(Hypothesis \vert Data) = \frac{P(Data \vert Hypothesis)P(Hypothesis)}{P(Data)}, ]

where $P(Hypothesis)$ is the prior, $P(Data \vert Hypothesis)$ is the likelihood of the Hypothesis, and $P(Hypothesis \vert Data)$ is the posterior, what answer our question: What is the probability of my Hypothesis according to the Data?.

[ P(Hypothesis \vert Data) \propto P(Data \vert Hypothesis) P(Hypothesis) ]


The second purpose is to give example on how to use stan and more precisely rstan which is the R interface to stan.

Winbugs is a very easy way to perform Bayesian modeling. And it is the freely available software used in the book Bayesian Methods for Ecology. There is many other ways to do bayesian modelling, and I'm certainly not the good person to say which one is the best. I strated with rstan and it gives me satisfaction.

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