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Data Scientist TJO in Tokyo

Data science, statistics or machine learning in broken English

BUGS / Stan

10+2 Data Science Methods that Every Data Scientist Should Know in 2016

Two years ago, I published a book -- written in Japanese so I'm afraid most of the readers can't read it :'( Actually this book was written as a summary of 10 major data science methods. But as two years have gone, the content of the book …

Bayesian modeling with R and Stan (5): Time series with seasonality

In the previous post, we successfully estimated a model with a nonlinear trend by using Stan. But please remember this is a time series dataset. Does it include any other kind of nonlinear components? Yes, we have to be careful for seasona…

Bayesian modeling with R and Stan (4): Time series with a nonlinear trend

The previous post reviewed how to estimate a simple hierarchical Bayesian models. You can see more complicated cases in a great textbook "The BUGS book". But personally hierarchical Bayesian modeling is the most useful for time-series anal…

Bayesian modeling with R and Stan (3): Simple hierarchical Bayesian model

In 2 previous posts, you learned what Bayesian modeling and Stan are and how to install them. Now you are ready to try it on some very Bayesian problems - as many people love - such as hierarchical Bayesian model. Definition of hierarchica…

Bayesian modeling with R and Stan (2): Installation and an easy example

The previous post overviewed what and how is Stan on R. Bayesian modeling with R and Stan (1): Overview - Data Scientist in Ginza, Tokyo Are you ready now? OK, this post reviews how to install Stan. Let's start here! :) In principle this p…

Bayesian modeling with R and Stan (1): Overview

Although I've written a series of posts titled "Machine Learning for package uses in R", usually I don't run machine learning on daily analytic works because my current coverage is so-called an ad-hoc analysis. Instead of machine learning,…