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The University of Washington is holding a web-based course which will be of interest to anyone who wants to learn about financial modeling with R: Financial Data Modeling and Analysis in R (AMATH 542) is a comprehensive introduction to the R statistical programming language for computational finance offered by the University ... [Read more...]

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If there are two (can be generalized to n) classes and both follow the same distribution (but with different parameters) it is possible to predict which class an observations comes from. Here I’ll try to predict a sample’s gender based on their height. The distribution of a person’... [Read more...]

Any frequent reader of R-bloggers will have come across several posts concerning the optimization of code - in particular, the avoidance of loops.Here's another aspect of the same issue. If you have experience programming in other languages besides R, this is probably a no-brainer, but for laymen, like myself, ... [Read more...]

There is a nice short article on memory issue in R at http://www.matthewckeller.com/html/memory.html. If you use R to process large data, you might find it helpful. It introduces: - checking how much memory an object is taking; - the memory … Continue reading → [Read more...]

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The Comprehensive R Archive Network, or CRAN for short, has been a major driver in the success and rapid proliferation of the R statistical language and environment. CRAN currently hosts around 3400 packages, and is growing at a rapid rate. Not too ... [Read more...]

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Last time we looked at the Matrix package and dug a little into the chol(), Cholesky Decomposition, function.  I noted that often in finance we do not have a positive definite (PD) matrix.  The chol() function in both the Base and Matrix... [Read more...]

The need to analyze time-series or other forms of streaming data arises frequently in many different application areas.  Examples include economic time-series like stock prices, exchange rates, or unemployment figures, biomedical data sequences like electrocardiograms or electroencephalograms, or industrial process operating data sequences like temperatures, pressures or concentrations.  As a ... [Read more...]

Here are the presentation slides I used for my talk on “Using R for Data Mining Competitions” at Ryerson University as part of the Greater Toronto Area (GTA) R User’s Meetup Group. Presentation (Prezi) Presentation (PDF) Meetup Event page Special thanks to Anthony Goldbloom from Kaggle and various competition ... [Read more...]

I follow some 80 odd people/ news sources on my twitter account. For a while I wondered which of these sources are most active on twitter. I picked a simple metric '# of status messages posted to twitter' as the measure of activity. Using R I quickly wrote a program to ... [Read more...]

I analyze a lot of experiments and there are many times when I want to quickly look at means and standard errors for each cell (experimental condition), or the same for each cell and individual-level attribute level (e.g., Democrat, Independent, … Continue reading → [Read more...]

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Only recently I discovered StackOverflow. I know, as a nerd already programming for many years that is quite late. For those who are not familiar with StackOverflow (aka SO), it is a Question and Answer site for programmers. It is… See more › [Read more...]

This is another pretty simple function, written to help me solve the simplest representation of a trivial but tedious task. Most biologist are probably familiar with this task. How many nucleotide differences exist between two given sequences? I only faced the easiest part of the problem, i.e. I do ... [Read more...]

Missing data hinders statistical analyses. Estimating missing values (imputation) prior to analysis is one way to deal with that. In some cases however, the missings need not be estimated at all, since they can be derived with certainty from other … Continue reading → [Read more...]