This post is based on a handout that I use for one of my courses, and it relates to the usual linear regression model, y = Xβ + ε In our list of standard assumptions about the error term in this linear multiple regression...

Paul Teetor, who is doing yeoman’s duty as one of the organizers of the Chicago R User Group (CRUG), asked recently if I would do a short presentation about a “favorite package”. I picked xlsx, one of the many packages that provides a bridge between spreadsheets and R. Here are the slides from my presentation

Last week, the New York Times published online an interactive tool to explore NFL draft picks, revealing the fact that there's not much relationship between an early pick and the star performers in the season: Kevin Quealy, graphics editor at the NYT, detailed the process behind creating this graphic on his chartsnthings blog. He and others on the graphics...

This is a ‘do over’ of a project I started while at my former employer in the fall of 2012. I presented part 1 of this framework at the FX Invest West Coast conference on September 11, 2012. I have made some changes and expanded the analysis since then. Part 2 is complete and will follow this post in...

Integrating Documentation and Calculation Integrating Documentation and Calculation This post is a first in that I've authored it using RStudio. I would guess most people who work in computational finance or quantitative risk are at least familiar with R. Unfortunately R as...

A client has a specific audit they perform quarterly across 200 of their manufacturing plants. The audit has 8 distinct sections examining the different areas of the plant (shipping, receiving, storage, packaging,etc.) Instead of having one cumulative final score, the audit displays a final score for each section. I wanted to examine the distribution of

Tree methods such as CART (classification and regression trees) can be used as alternatives to logistic regression. It is a way that can be used to show the probability of being in any hierarchical group. The following is a compilation of many of the key R packages that cover trees and forests. The goal here