This post is part of a running series on Bayesian MCMC tutorials. For updates, follow @StableMarkets. Metropolis Review Metropolis-Hastings is an MCMC algorithm for drawing samples from a distribution known up to...continue reading.
This post is part of a running series on Bayesian MCMC tutorials. For updates, follow @StableMarkets. Metropolis Review Metropolis-Hastings is an MCMC algorithm for drawing samples from a distribution known up to...continue reading.
For More posts on Bayesian models, Bayesian Nonparametrics, and causal inference follow me on twitter @stablemarkets. My advisor and his collaborator are teaching a short course on Bayesian Nonparametric Methods...continue reading.
Previous posts in this series on MCMC samplers for Bayesian inference (in order of publication): Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for...continue reading.
Previous posts in this series on MCMC samplers for Bayesian inference (in order of publication): Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for...continue reading.
First off, here are the previous posts in my Bayesian sampling series: Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for Bayesian Multiple Linear...continue reading.
In a previous post, I derived and coded a Gibbs sampler in R for estimating a simple linear regression. In this post, I will do the same for multivariate linear...continue reading.
Many introductions to Bayesian analysis use relatively simple didactic examples (e.g. making inference about the probability of success given bernoulli data). While this makes for a good introduction to Bayesian...continue reading.
I came across a stackoverflow post the other day touching on first differencing and decided to write a quick review of the topic as well as related random effects and...continue reading.
The recent flare-up in discussions on p-values inspired me to conduct a brief simulation study. In particularly, I wanted to illustrate just how p-values vary with different effect and sample sizes. Here are...continue reading.
In my last post, I compiled and cleaned publicly available data on over 4.5 million stops over the past 11 years. I also presented preliminary summary statistics showing that blacks had...continue reading.
I first became interested in networks when reading Matthew O’Jackson’s 2010 paper describing their application to economics. During the 2014 ebola outbreak, there was a lot of concern over the disease spreading to the...continue reading.
In this post I will extend a previous analysis creating a borough-level heat map of NYC motor vehicle collisions. The data is from NYC Open Data. In particular, I will go from borough-level...continue reading.
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
