Teaching

Some Teaching Material:

1. Lecture notes on Statistical Inference. [GitHub]

2. Applying for a PhD?  [pdf slides] 

3.  The Normal-Normal Bayesian model (known variance). (R Markdown)

4.  The Beta-Binomial model. (R Markdown)

5.  Predictive Beta Binomial distribution. (R Markdown)

6.  Frequentist vs Noninformative Bayesian inference in the Binomial model. (R Markdown)

7.  Some visual tools for comparing two univariate samples. (R Markdown)

8.  Maximum likelihood estimation in the logistic regression model. (R Markdown)

9.  Method of moments for the Kumaraswamy distribution. (R Markdown)

10.  Performance of normal CIs for log-odds. (R Markdown)

11.  Profile likelihood confidence intervals for the parameters of the normal distribution. (R Markdown)

12.  A Brief analysis of the Challenger data. (R Markdown)

13.  Wald Confidence Interval for the Normal distribution. (R Markdown)

14.  Binomial Trial: Bayesian Analysis. (R Markdown)

15.  Robust Estimation of Scale. (R Markdown)

16.  Robust Estimation of Location. (R Markdown)

17.  Robust Outlier Detection. (R Markdown)

18.  Permutation test: examples. (R Markdown)

19.  Paired differences: the Darwin data. (R Markdown)

20.  Unpaired observations: Mosquitoes data. (R Markdown)

21.  MLE Logistic Distribution. (R Markdown)

22.  Likelihood Ratio Test: Skew Normal vs Normal. (R Markdown)

23.  The Kumaraswamy Distribution. (R Markdown)

24.  Simulating from a Bivariate Gaussian Copula. (R Markdown)

25.  The Cox Proportional Hazards Model and the Partial Likelihood function. (R Markdown)

26.  The Hyperbolic Secant Distribution. (R Markdown)

27.  Bayesian inference on the two-piece normal distribution using rstan. (R Markdown)

28.  Quick parallelisation of a for loop. (R Markdown)

29.  Simulation of correlated covariates: implementation and a warning. (R Markdown)

30.  The Generalised Gamma Distribution. (R Markdown)

31. Bivariate Distributions with twopiece and double twopiece marginals. (R Markdown)

32. Downloading financial data from Yahoo! Finance in R. (R Markdown)

33. Bayesian survival analysis using a General Hazard Structure. (R Markdown)

34.  Fitting the two-piece normal distribution to the Volcanoes dataset. (R Markdown)

35.  Approximating the Beta PDF with a Kumaraswamy PDF based on the TV distance. (R Markdown)

36.  HazReg: Parametric Hazard-based regression models for survival data. (R Markdown)

37.  The Nelson-Aalen estimator. (R Markdown)

38. Estimation of the shape parameter of the Zeta Distribution. (R Markdown)

39. (Approximate) Maximum Likelihood Estimation for the Conway-Maxwell-Poisson Distribution. (R Markdown)

40. Profile-likelihood based confidence intervals in Sample Selection models, (R Markdown)

Short courses:

1.   An Introduction to MCMC. [Slides]  [R Markdown]

2. Short course on Parametric Survival Analysis. (GitHub repository)

3.  Bayesian variable selection for survival data. (GitHub repository)