Links that are useful

https://www.statlearning.com/, a book to be downloaded to learn statistics and apply in R.

https://towardsdatascience.com/maximum-likelihood-ml-vs-reml-78cf79bef2cf, a mathematical explanation showing the difference between ML and REML with exact formulas.

https://topepo.github.io/caret/, package for cross-validation or leave-one-out

GLMnet and penalized are packages for penalization and regularization : https://glmnet.stanford.edu/articles/glmnet.html and https://cran.r-project.org/web/packages/penalized/index.html

https://rpubs.com/yjunechoe/correlationsLMEM, about correlation in mixed-effect models

https://library.virginia.edu/data/articles/understanding-deviance-residuals, understanding deviance residuals

formula for acf https://www.sciencedirect.com/topics/chemistry/autocorrelation-function

https://stats.stackexchange.com/questions/92394/checking-residuals-for-normality-in-generalised-linear-models on checking normality in GLMs

comparison of link functions https://watermark.silverchair.com/020083_1_online.pdf