UCSC - Bayesian Statistics: Capstone Project
- Offered byCoursera
Bayesian Statistics: Capstone Project at Coursera Overview
Duration | 12 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Credential | Certificate |
Bayesian Statistics: Capstone Project at Coursera Highlights
- Earn a Certificate upon completion
Bayesian Statistics: Capstone Project at Coursera Course details
- This is the capstone project for UC Santa Cruz's Bayesian Statistics Specialization
- It is an opportunity for you to demonstrate a wide range of skills and knowledge in Bayesian statistics and to apply what you know to real-world data
- You will review essential concepts in Bayesian statistics with lecture videos and quizzes, and you will perform a complex data analysis and compose a report on your methods and results
Bayesian Statistics: Capstone Project at Coursera Curriculum
Bayesian Conjugate Analysis for Autogressive Time Series Models
Introduction
Model Formulation
Prediction for AR Models
Prerequisite skill checklist
Read Data
Review: Useful Distributions
Posterior Distribution Derivation
AR model fitting example
AR model prediction example
Extended AR model
Practice Quiz for Week 1
First step for the project
Model Selection Criteria
AIC and BIC in selecting the order of AR process
Deviance information criterion (DIC)
AIC and BIC example
DIC Example
Determine the order of your data
Calculate DIC for single AR model
Bayesian location mixture of AR(P) model
Prediction for Location Mixture of AR Models
Full conditional distributions of model parameters
Coding the Gibbs sampler
Prediction for location mixture of AR model
Sample code for the Gibbs sampler
Determine the number of components
Location and scale mixture of AR model
Fit a location mixture of AR model
Determine number of components for the mixture model
Peer-reviewed data analysis project
Acknowledgments and Reference