April 2013

Review: Kölner R Meeting 12 April 2013

April 23, 2013 | 0 Comments

Our 5th Cologne R user group meeting was the best attended meeting so far, with 20 members finding their way to the Institute of Sociology for two talks by Diego de Castillo on shiny and Stephan Holtmeier on cluster analysis, followed by beer and schnitzel at the Lux, a gastropub nearby.... [Read more...]

Installation of WRS package (Wilcox’ Robust Statistics)

April 22, 2013 | 0 Comments

Some users had trouble installing the WRS package from R-Forge. Here’s a method that should work automatically and fail-safe: ?View Code RSPLUS# first: install dependent packages install.packages(c("MASS", "akima", "robustbase"))   # second: install suggested packages install.packages(c("cobs", "robust", "mgcv", "scatterplot3d", "quantreg", "rrcov", "lars", "pwr", "trimcluster", "... [Read more...]

Adding Percentiles to PDQ

April 22, 2013 | 0 Comments

Pretty Damn Quick (PDQ) performs a mean value analysis of queueing network models: mean values in; mean values out. By mean, I mean statistical mean or average. Mean input values include such queueing metrics as service times and arrival rates. These could be sample means. Mean output values include such ... [Read more...]

Upcoming GDAT Class May 6-10, 2013

April 22, 2013 | 0 Comments

Enrollments are still open for the Level III Guerrilla Data Analysis Techniques class to be held during the week May 6—10. Early-bird discounts are still available. Enquire when you register. As usual, all classes are held at our lovely Larkspur... [Read more...]

Time Varying Higher Moments with the racd package.

April 22, 2013 | 0 Comments

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have ... [Read more...]

R et Twitter

April 22, 2013 | 0 Comments

[This article was first published on Learning Data Science , and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share [Read more...]

2D plot with histograms for each dimension (2013 edition)

April 22, 2013 | 0 Comments

In 2009, I wrote about a way to show density plots along both dimensions of a plot. When I ran the code again to adapt it to a new project, it didn't work because ggplot2 has become better in the meantime. Below is the updated code. Using the gridExtra...
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garch and the distribution of returns

April 22, 2013 | 0 Comments

Using garch to learn a little about the distribution of returns. Previously There are posts on garch — in particular: A practical introduction to garch modeling The components garch model in the rugarch package garch and long tails There has also been discussion of the distribution of returns, including a satire ... [Read more...]

Data Analysis for Marketing Research with R Language (1)

April 22, 2013 | 0 Comments

Data Analysis technologies such as t-test, ANOVA, regression, conjoint analysis, and factor analysis are widely used in the marketing research areas of A/B Testing, consumer preference analysis, market segmentation, product pricing, sales driver analysis, and sales forecast etc. Traditionally the analysis tools are mainly SPSS and SAS, however, the ... [Read more...]

You Can Quote Me on That

April 21, 2013 | 0 Comments

The other day I came across the Empirical Quotes page on Mark Byran's blog. Some of his quotes related specifically to econometrics, and I thought I'd share a few others. That certainly doesn't mean that I agree with them all! "It is the preparation skill of the econometric chef that ... [Read more...]

What Is the Probability of a 16 Seed Beating a 1 Seed?

April 21, 2013 | 0 Comments

Note: I started this post way back when the NCAA men's basketball tournament was going on, but didn't finish it until now. Since the NCAA Men's Basketball Tournament has moved to 64 teams, a 16 seed as never upset a 1 seed. You might be tempted to say ... [Read more...]

Ordinal data, models with observers

April 21, 2013 | 0 Comments

I recently made three posts regarding analysis of ordinal data. A post looking at all methods I could find in R, a post with an additional method and a post using JAGS. Common in all three was using the cheese data, a data set where... [Read more...]
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