This text provides R tutorials on statistics, including hypothesis testing, ANOVA and linear regression. It fulfills popular demands by users of r-tutor.com for exercise solutions and offline access.
Part III of the text is about Bayesian statistics. It begins with closed analytic solutions and basic BUGS models for simple examples. Then it covers OpenBUGS for Bayesian ANOVA and regression analysis. Finally, it shows how to build more complex Bayesian models and demonstrates CODA for Markov Chain Monte Carlo (MCMC) convergence.
The last part of this text discusses advanced GPU computing in R using the RPUDPLUS package. Topics include hierarchical clustering, Kendall's tau, support vector machines and Bayesian classification. It illustrates the importance of High Performance Computing (HPC) in the future of statistics. The text concludes with a new section on hierarchical multinomial logit model for marketing research.
Part III of the text is about Bayesian statistics. It begins with closed analytic solutions and basic BUGS models for simple examples. Then it covers OpenBUGS for Bayesian ANOVA and regression analysis. Finally, it shows how to build more complex Bayesian models and demonstrates CODA for Markov Chain Monte Carlo (MCMC) convergence.
The last part of this text discusses advanced GPU computing in R using the RPUDPLUS package. Topics include hierarchical clustering, Kendall's tau, support vector machines and Bayesian classification. It illustrates the importance of High Performance Computing (HPC) in the future of statistics. The text concludes with a new section on hierarchical multinomial logit model for marketing research.
