# Logistic regression with categorical data in Ruby

I had some fun analysing the shelter animal data from kaggle using the Ruby gems daru for data wrangling and statsample-glm for model fitting. In this blog post, I want to demonstrate that data wrangling and statistical modeling is not an area of absolute predominance of Python and R, but that it is possible in Ruby too (though, currently to a much lesser extent).

# NMatrix with Intel MKL on my university's HPC

In order to use NMatrix for the statistical analysis of big genomic data, I decided to install it on my university’s high performance computing system (HPC). It is called Cypress (like the typical New Orleans tree), and it’s currently the 10th best among all American universities.

# Statistical linear mixed models in Ruby with mixed_models (GSoC2015)

Google Summer of Code 2015 is coming to an end. During this summer, I have learned too many things to list here about statistical modeling, Ruby and software development in general, and I had a lot of fun in the process!

# A (naive) application of linear mixed models to genetics

The following shows an application of class LMM from the Ruby gem mixed_models to SNP data (single-nucleotide polymorphism) with known pedigree structures. The family information is prior knowledge that we can model in the random effects of a linear mixed effects model.

# P-values and confidence intervals

A few days ago I started working on hypotheses tests and confidence intervals for my project mixed_models, and I got pretty surprised by certain things.

# MixedModels Formula Interface and Categorical Variables

I made some more progress on my Google Summer of Code project MixedModels. The linear mixed models fitting method is now capable of handling non-numeric (i.e., categorical) predictor variables, as well as interaction effects. Moreover, I gave the method a user friendly R-formula-like interface. I will present these new capabilities of the Ruby gem with an example. Then I will briefly describe their implementation.

# Model specification for linear mixed model

Last week I wrote about my implementation of an algorithm that fits a linear mixed model in Ruby using the gem MixedModels, that I am working on right now. See, first rudimentary LMM fit.

# A rudimentary first linear mixed model fit

During the last two weeks I made some progress on my Google Summer of Code project. The Ruby gem is now capable of fitting linear mixed models. In this short blog post I want to give an example, and compare the results I get in Ruby to those obtained by lme4 in R.

# Solve two-point boundary value problems in Ruby with spitzy

A few days ago I programmed a numerical method for the solution for two-point boundary value problems, and today I discovered that I can use MathJax to display mathematical formulas in here (although there are some inconveniences related to the use of underscores). So, here goes another blog post!

# Solve ODEs in Ruby with spitzy

Over the weekend I have written a couple of numerical solvers for one-dimensional initial value problems in Ruby, and added them to my project spitzy.

A couple of days ago I started working on a collection of numerical methods for differential equations, wirtten in pure Ruby (I have conviced the professor of my numerical DE class that thats a good idea for my final project in said class).
Recently I got surprised by the behaviour of #permute_columns` in the Ruby gem NMatrix.