Bayesian Method with R - Oct 2

Bayesian Method with R - Oct 2

Posted by manager

Updated: Oct 3, 2014

1. Intro:

Vivian will cover the following topic using R:
• write short scripts to define a Bayesian model
• use or write functions to summarize a posterior distribution
• use functions to simulate from the posterior distribution
• construct graphs to illustrate the posterior inference

And she will show a few real world applications of Bayesian modeling.

2. Speaker:

Vivian Zhang, CTO of SupStat Inc which is a data analytic consulting firm.

3. Perquisites:

Basic R programming background.

4. Scenario Review:

Explanation will be provided subsequent sections.

5. Relevant Materials:

    1) Meetup slides:

    2) Meetup video:

3) ACF plot reading:­

4) Metropolis Hastings algorithm:­

5) Gibbs Sampling:­





10) NaiveBayes from e1091 packakge:

11) event link:

6. Further Information:

Twitter: @Vivian__Zhang  @SupStat  @NycDataSci

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