Publications by Hao Wei

HaoWei_ANLY 505-51- B-2021/Late Summer

02.08.2021

Chapter 3 - Sampling the Imaginary This chapter introduced the basic procedures for manipulating posterior distributions. Our fundamental tool is samples of parameter values drawn from the posterior distribution. These samples can be used to produce intervals, point estimates, posterior predictive checks, as well as other kinds of simulations. Po...

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HaoWei_ANLY 505-51- B-2021/Late Summer

02.08.2021

Chapter 2 - Large Worlds and Small Worlds The objectives of this problem set is to work with the conceptual mechanics of Bayesian data analysis. The target of inference in Bayesian inference is a posterior probability distribution. Posterior probabilities state the relative numbers of ways each conjectured cause of the data could have produced th...

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Assignment #10 - Monsters and Mixtures_ANLY 505-51- B-2021/Late Summer - Data Sim Bayesian Mod & Infer_Hao_Wei

06.10.2021

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...

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ANLY 505-51- B-2021/Late Summer - Data Sim Bayesian Mod & Infer_assignemnt 5

30.08.2021

Chapter 6 - The Haunted DAG & The Causal Terror Multiple regression is no oracle, but only a golem. It is logical, but the relationships it describes are conditional associations, not causal influences. Therefore additional information, from outside the model, is needed to make sense of it. This chapter presented introductory examples of some com...

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ANLY 505-51- B-2021/Late Summer - Data Sim Bayesian Mod & Infer_assignment 4

24.08.2021

Chapter 5 - Many Variables and Spurious Waffles This chapter introduced multiple regression, a way of constructing descriptive models for how the mean of a measurement is associated with more than one predictor variable. The defining question of multiple regression is: What is the value of knowing each predictor, once we already know the other pr...

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ANLY 505-51- B-2021/Late Summer - Data Sim Bayesian Mod & Infer_assignemnt 6

07.09.2021

Chapter 7 - Ulysses’ Compass The chapter began with the problem of overfitting, a universal phenomenon by which models with more parameters fit a sample better, even when the additional parameters are meaningless. Two common tools were introduced to address overfitting: regularizing priors and estimates of out-of-sample accuracy (WAIC and PSIS)...

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Assignment #9 - God Spiked the Integers_ANLY 505-51- B-2021/Late Summer - Data Sim Bayesian Mod & Infer_Hao_Wei

06.10.2021

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...

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