Publications by Jiaoyuan Huang
Document
Chapter 9 - Markov Chain Monte Carlo This chapter has been an informal introduction to Markov chain Monte Carlo (MCMC) estimation. The goal has been to introduce the purpose and approach MCMC algorithms. The major algorithms introduced were the Metropolis, Gibbs sampling, and Hamiltonian Monte Carlo algorithms. Each has its advantages and disadva...
3382 sym R (17958 sym/44 pcs) 5 img
Document
Please do not reorder the assignment - fill in each chunk as requested. Load the libraries + functions Load all the libraries or functions that you will use to for the rest of the assignment. It is helpful to define your libraries and functions at the top of a report, so that others can know what they need for the report to compile correctly. ##...
1844 sym R (8090 sym/44 pcs)
Document
Load the libraries + functions Load all the libraries or functions that you will use to for the rest of the assignment. It is helpful to define your libraries and functions at the top of a report, so that others can know what they need for the report to compile correctly. Import the separate python file that includes the functions you will need ...
2361 sym R (4518 sym/22 pcs)
Document
Chapter 11 - God Spiked the Integers This chapter described some of the most common generalized linear models, those used to model counts. It is important to never convert counts to proportions before analysis, because doing so destroys information about sample size. A fundamental difficulty with these models is that parameters are on a different...
3135 sym R (2787 sym/17 pcs) 1 img
Document
Chapter 12 - Monsters and Mixtures This chapter introduced several new types of regression, all of which are generalizations of generalized linear models (GLMs). Ordered logistic models are useful for categorical outcomes with a strict ordering. They are built by attaching a cumulative link function to a categorical outcome distribution. Zero-inf...
3625 sym R (12441 sym/24 pcs) 2 img