osazuwa
Robert Ness
Recently Published
Probabilistic Causal Attribution Sandbox
Experimenting with various metrics for causal attribution.
rephrasing eval
draft of an eval on where classifications on utterances are compared to classifications on rephrasings of that utterance.
Introduction to Causal Reasoning on DAGS
Introduction to causal reasoning with DAGs with the bnlearn package.
Bayesian causal vs anti-causal
An experiment in using Bayesian analysis to distinguish between causal and anti-causal models
Basic Deconfound Analysis
A VERY basic deconfounder analysis on Movielens data
Causal Generative Modeling with Bayesian Networks and R’s bnlearn package
An introduction to causal directed graphs using bnlearn
Introduction to Causal Reasoning on DAGS
An introduction to key graphical concepts with the DAG and how they relate to causal reasoning.
Causal inference with causal Bayesian networks and R’s bnlearn package
A simple illustration of how to construct a causal effect query using R's bnlearn package.
lme4 syntax and Stan
A intro to lme4 systax and how it maps to a stan multilevel model
BAPP#1: Intro to bsts
bsts is an open source R package from Google. It enables one to assemble a time series model from components familiar to forecasters, namely periodic and seasonal trends, as as regression components that capture correlation between different time series.
Exploration of College Data
A quick exploration of the college score card data.
ggplot2_homework
Some practice questions accompanying http://rpubs.com/osazuwa/ggplot2
Introduction to ggplot2
A quick intro to ggplot2 and the concept of layering visualizations.
cpd-modeling-outline
proposal for a paper
