oliviergimenez/statistics-for-ecologists-Master-courses 开源项目中文解读：技术栈、适用场景与上手建议

Creative Commons Attribution 4.0 International

项目介绍

oliviergimenez/statistics-for-ecologists-Master-courses 是一个托管在 GitHub 上的开源项目，主要使用 R 编写，采用 Creative Commons Attribution 4.0 International 许可证，目前获得 62 个 Star、11 次 Fork。

仓库全名: oliviergimenez/statistics-for-ecologists-Master-courses
开源许可证: Creative Commons Attribution 4.0 International
Star 数: 62
Fork 数: 11

README 摘要

Statistics for ecologists You will find here the material for a course I give every year to Master students at University of Montpellier. Topics covered Distributions (22-59) and likelihoods (60-84) Hypothesis testing (85-106) and multimodel inference (107-125) Introduction to Bayesian inference (126-179) Generalized Linear Models GLMs (180-244) Generalized Additive Models GAMs (245-247) Mixed Effect GLMMs and GAMMs…

完整内容见 GitHub 原始 README 或本页。

常见问题

statistics-for-ecologists-Master-courses 用什么语言开发？

主要使用 R 编写，采用 Creative Commons Attribution 4.0 International 许可证，目前有 62 个 Star。

statistics-for-ecologists-Master-courses 可以免费商用吗？

仓库标注的许可证为 Creative Commons Attribution 4.0 International，商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 statistics-for-ecologists-Master-courses 的源码？

可以直接克隆仓库：git clone https://github.com/oliviergimenez/statistics-for-ecologists-Master-courses.git；安装与运行步骤见仓库 README。

statistics-for-ecologists-Master-courses 最近还在维护吗？

仓库最近一次更新为 2025年3月11日，当前没有未关闭的 Issue；Star 数为 62，可作为社区活跃度的参考。

关于

The material for a course on Statistics for ecologists I teach every year to Master students.

描述取自 GitHub 官方 API，中文内容由 GitRead 中文社区编辑团队整理。

简要分析

热度分

146

价值分

活跃状态

活跃

bayesian-inference glmm statistics-course

GitHub

README

Statistics for ecologists

You will find here the material for a course I give every year to Master students at University of Montpellier.

Topics covered

Distributions (22-59) and likelihoods (60-84)
Hypothesis testing (85-106) and multimodel inference (107-125)
Introduction to Bayesian inference (126-179)
Generalized Linear Models GLMs (180-244)
Generalized Additive Models GAMs (245-247)
Mixed Effect GLMMs and GAMMs (248-306)

How to use this repo?

The PDF of the lecture slides can be downloaded here
The practicals are here and the solutions there
The videos are also available (in French) on Youtube here:
- Lecture 1 covering slides 1-140 download here
- Lecture 2 covering slides 140-180 download here
- Lecture 3 covering slides 180-245 download here
- Lecture 4 covering slides 245-305 download here
The R codes I use in the lectures and the practicals are also provided here and there respectively
To download the whole repo on your computer, click on the Code green button at the top right of the page and choose Download ZIP
Alternatively, click on same green button to create a copy of the repo within your own GitHub account (clone)

Problem

If you spot a typo or an error, find a bug, or have trouble running the code, please file an issue or get back to me.

Licence / License

This work is licensed under a Creative Commons Attribution 4.0 International License

To-do list

Besides books, add a few relevant papers and pointers to videos
- On GLMs, O’Hara’s paper https://doi.org/10.5735/086.046.0205
- On GLMMs, Bolker’s TREE paper https://doi.org/10.1016/j.tree.2008.10.008 and FAQ https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html
- On Bayesian analyses, McElreath lectures and videos https://github.com/rmcelreath/statrethinking_winter2019
Include more ecological examples, and maybe use just one or two examples throughout
Consider an example mixing continuous and discrete explanatory variables
Illustrate how to report results
- Have a look to recent papers in the journal you’re targeting
- Check out Zuur’s books
- Read http://bit.ly/2v9dAI8
Introduce the tidyverse. Or refer to some material I wrote https://github.com/oliviergimenez/intro_tidyverse

statistics-for-ecologists-Master-courses