# Models by Example

Roll your own to understand more.

Michael Clark https://m-clark.github.io
2020-11-30

# New Book

I’ve completed a new bookdown document, Models by Example, that converts most of the code from my Miscellaneous R repo. I initially just wanted to update the code, but decided to use a more formal approach to make it cleaner and more accessible. It’s mostly complete, though may be added to on rare occasion, and further cleaned as I find annoying bits here and there. Each topic contains ‘by-hand’ demonstration, such that you can see conceptually how a model is estimated, or technique employed. This can help those that want to dive a little deeper to get a peek behind the curtain of the functions and packages they use, hopefully empowering them to go further with such models.

Topics covered include the following, and I plan to post a sample chapter soon.

##### Models
• Linear Regression
• Logistic Regression
• One-factor Mixed Model
• Two-factor Mixed Model
• Mixed Model via ML
• Probit & Bivariate Probit
• Heckman Selection
• Marginal Structural Model
• Tobit
• Cox Survival
• Hurdle Model
• Zero-Inflated Model
• Naive Bayes
• Multinomial
• Ordinal
• Markov Model
• Hidden Markov Model
• Quantile Regression
• Cubic Spline Model
• Gaussian Processes
• Neural Net
• Extreme Learning Machine
• Reproducing Kernel Hilbert Space Regression
• Confirmatory Factor Analysis
##### Bayesian
• Basics
• Bayesian t-test
• Bayesian Linear Regression
• Bayesian Beta Regression
• Bayesian Mixed Model
• Bayesian Multilevel Mediation
• Bayesian IRT
• Bayesian CFA
• Bayesian Nonparametric Models
• Bayesian Stochastic Volatility Model
• Bayesian Multinomial Models
• Variational Bayes Regression
• Topic Model
##### Estimation
• Maximum Likelihood
• Penalized Maximum Likelihood
• L1 (lasso) regularization
• L2 (ridge) regularization
• Newton and IRLS
• Expectation-Maximization
• Metropolis Hastings
• Hamiltonian Monte Carlo

### Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

### Reuse

Text and figures are licensed under Creative Commons Attribution CC BY-SA 4.0. Source code is available at https://github.com//m-clark/m-clark.github.io, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

### Citation

`Clark (2020, Nov. 30). Michael Clark: Models by Example. Retrieved from https://m-clark.github.io/posts/2020-11-30-models-by-example/`
```@misc{clark2020models,