My intuition tells me that objects traveling through the air would meet more resistance when there is more moisture in the air. It turns out that my intuition is wrong. It still doesn’t make sense to me but apparently humid … Continue reading →

I have become quite a big fan of graphics that combine the features of traditional figures (e.g. bar charts, histograms, etc.) with tables. That is, the combination of numerical results with a visual representation has been quite useful for exploring descriptive statistics. I have wrapped two of my favorites (build around ggplot2) and included them as part

Here's a cool application of calendar heat maps: runner Andy used R to catalogue his daily running mileage over the last 2+ years: There are lots of ways to chart data like this (a simple time-series chart, for example), but sometimes looking at data in new ways offers fresh perspectives. For example, Andy notes: "Apparently I missed running on...

Small changes in the input assumptions often lead to very different efficient portfolios constructed with mean-variance optimization. I will discuss Resampling and Covariance Shrinkage Estimator – two common techniques to make portfolios in the mean-variance efficient frontier more diversified and immune to small changes in the input assumptions. Resampling was introduced by Michaud in Efficient

Time Series as calendar heat maps + All of my running data since April 1, 2009 = Generated by the following code: #Sample Code based on example program at: source(file = "calendarHeat.R") run<- read.csv("log.csv", header = TRUE, sep=",") sum(run$Distance) date <- c() for (i in 1: dim(run)){ if(run$DistanceUnit== 'Kilometer'){ miles <- c(miles,run$Distance * 0.62) }

Today I needed to cut out a rectangle of geologic data from a state-wide map in an AEA coordinate system, using a bounding box from a UTM zone 10 region, with the output saved in UTM zone 10 coordinates. PostGIS makes this type of operation very simple...

In case you missed them, here are some articles from October of particular interest to R users. The creator of the ggplot2 package, Hadley Wickham, shares details on some forthcoming big-data graphics functions (based on research sponsored by Revolution Analytics). A list of several dozen free data sources that can easily be imported into R. Bob Muenchen gave a...