Standard nonlinear regression assumes homoscedastic data, that is, all response values are distributed normally.  In case of heteroscedastic data (i.e. when the variance is dependent on the magnitude of the data), weighting the fit is essential. In nls (or nlsLM of the minpack.lm package), weighting can be conducted ... [Read more...]

This post presents the video of a talk that I presented in July 2012 at Melbourne R Users on using knitr, R Markdown, and R Studio to perform reproducible analysis. I also provide links to a github repository where the R markdown examples can be examin... [Read more...]

We extend the analysis of part 7 by calculating the final wealth for all tuples of 3 and 4 stocks, this is a simple extension but it also shows the most important problem of the Universal portfolio algorithm, its exponential complexity in the number of... [Read more...]

At the upcoming 2012 summer meeting of the Society of Political Methodology, I will be presenting a poster on Isarithmic Maps of Public Opinion. Since last posting on the topic, I have made major improvements to the code and robustness of the modeling approach, and written a tutorial that illustrates the ... [Read more...]

Say we have some following raw data. It consists of a timestamp and a corresponding value. There is a peak at exactly midnight (00:00:00). Each timestamp is fully specified. It contains a date, a time of day, and a time zone offset indication. In this case +0000, meaning the data is 0 hours ... [Read more...]

Here are the slides for the first day of my course at Monash University, Melbourne, in the Special Lectures in Econometrics, with a strong similarity with the slides of my course in Wharton, two years ago. (Be sure to check slide 67! If the update on slideshare works from my flat ... [Read more...]

Surveys become engaging when they become games, or at least, take on some of the characteristics of games.  This is the argument made by those advocating the gamification of marketing research [http://researchaccess.com/2011/12/market-researc... [Read more...]

Motived by the post from FlowingData(http://flowingdata.com/2010/11/23/how-to-make-bubble-charts/), I made this plot with R code below:par(mfrow=c(3,1), mar=c(4,6,4,4))for(ty in c("protein_coding","lincRNA","piRNA")){          ... [Read more...]

The US News best hospital 2012-20132 rankings are out. The big news is that Johns Hopkins has lost its throne. For 21 consecutive years Hopkins was ranked #1, but this year Mass General Hospital (MGH) took the top spot displacing Hopkins to #2. Howeve... [Read more...]

In most data science applications, preparing the data is at least half the job. Finding where the data lives, figuring out how to access it, finding the right records, filtering, cleaning and transforming the data ... all of this has to be done before the statistical analysis can even begin. Fortunately, ... [Read more...]

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Computing for Data Analysis Data Analysis Mathematical Biostatistics Bootcamp [Read more...]

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The 15th problem in Project Euler. Starting in the top left corner of a 22 grid, there are 6 routes (without backtracking) to the bottom right corner. How many routes are there through a 2020 grid? Mmm… walk in the … Continue reading → [Read more...]

Sometimes you just want to see what all the fuss is about. File this under the 'because I can' category: I proudly (?) present - a wordcloud produced from the text of E. L. James' "50 Shades of Grey".For a book which is getting all this press about bei... [Read more...]

Last time around I used R to plot the average runs per game for the American League, starting in 1901. Now I’ll do the same for the National League.  I'll save a comparison of the two leagues for my next post.A fundamental principal of programming is that code can ... [Read more...]

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Today I’m going to adress a fairly common problem in ecology that has been coming up frequently as of late. The issue is how to create a site x species matrix for community composition analysis (i.e. ordination). Moreover, ecologists have to do … Continue reading → [Read more...]

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John Myles White, self-described "statistics hacker" and co-author of "Machine Learning for Hackers" was interviewed recently by The Setup. In the interview, he describes his some of his go-to R packages for data science: Most of my work involves programming, so programming languages and their libraries are the bulk of ... [Read more...]