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David Makowski's Projects

agroecological-modelling icon agroecological-modelling

Short introductory lecture on modelling in agro-ecology. The lecture presents different types of models, their interests, and their limits. It explains the main steps of a modelling project and provides several principles to become a "good" modeller. The repository also includes a figure illustrating the risk of overfitting a model (very common). The R code used to produce this figure is provided as well.

basics-of-bayesian-statistics icon basics-of-bayesian-statistics

This course includes three parts: (1) Main principles of Bayesian statistics (Bayes rule, Prior, Likelihood, MCMC...), (2) Bayesian regression (model formulation, inference with MCMC), (3) Model evaluation.

bayesian-metaanalysis icon bayesian-metaanalysis

Application of simple Bayesian hierarchical models to assess the impact of climate change on wheat yields

codepaper2ndordermas icon codepaper2ndordermas

R codes used in the paper "Synthesising results of meta-analyses to inform policy: a comparison of fast-track methods"

generalized-linear-model icon generalized-linear-model

This course presents several standard generalized linear models (GLM) and explain how GLM can be used to analyze categorical data. Methods for parameter estimation and model evaluation are decribed and several examples in agronomy and ecology are presented to illustrate key concepts. The course is available in the file GLM_2021.pdf.

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