Preface
I BASIC STATISTICS FOR ECOLOGISTS
1 Introduction to PART I
- 1.1 Further reading
2 Basics of statistics
3 Data analysis step by step
4 Probability distributions
5 Transformations
6 Reproducible research
- 6.1 Summary
- 6.2 Further reading
7 Further topics
II BAYESIAN DATA ANALYSIS
8 Introduction to PART II
- Further reading
9 The Bayesian paradigm and likelihood in a frequentist and Bayesian framework
10 Prior distributions and prior sensitivity analyses
11 Normal Linear Models
12 Assessing model assumptions
13 Linear mixed effect models
14 Generalized linear models
15 Generalized linear mixed models
16 Posterior predictive model checking
17 Model comparison and multimodel inference
18 MCMC using Stan via rstanarm, brms or rstan
19 Ridge Regression
20 Structural equation models
- 20.1 Introduction
21 Modeling spatial data using GLMM
- 21.1 Introduction
- 21.2 Summary
III ECOLOGICAL MODELS
22 Introduction to PART III
- 22.1 Model notations
23 Zero-inflated Poisson mixed model
24 Daily nest survival
25 Capture-mark recapture model with a mixture structure to account for missing sex-variable for parts of the individuals
26 What sample size?
- 26.1 Introduction
IV APPENDICES
Referenzen

Bayesian Data Analysis in Ecology with R and Stan

19 Ridge Regression

We, here best direct readers to the very useful article and R-package:

https://glmnet.stanford.edu/articles/glmnet.html