Monthly Archives: March 2014

Bayesian Data Analysis [BDA3 - part #2]

March 30, 2014
By
Bayesian Data Analysis [BDA3 - part #2]

Here is the second part of my review of Gelman et al.’ Bayesian Data Analysis (third edition): “When an iterative simulation algorithm is “tuned” (…) the iterations will not in general converge to the target distribution.” (p.297) Part III covers advanced computation, obviously including MCMC but also model approximations like variational Bayes and expectation propagation

Read more »

The freqparcoord Package for Multivariate Visualization

March 30, 2014
By
The freqparcoord Package for Multivariate Visualization

Recently my student Yingkang Xie and I have developed freqparcoord, a novel approach to the parallel coordinates method for multivariate data visualization.  Our approach: Addresses the screen-clutter problem in parallel coordinates, by only plotting the “most typical” cases, meaning those with the highest estimated multivariate density values. This makes it easier to discern relations between variables.

Read more »

New Blog on R, Statistics, Data Science and So On

March 30, 2014
By
New Blog on R, Statistics, Data Science and So On

Hi, Norm Matloff here. I’m a professor of computer science at UC Davis, and was a founding member of the UCD Dept. of Statistics. You may know my book, The Art of R Programming (NSP, 2011).  I have some strong views on statistics–which you are free to call analytics, data science, machine learning or whatever your favorite term is–so

Read more »

Looking at Measles Data in Project Tycho

March 30, 2014
By
Looking at Measles Data in Project Tycho

Project Tycho includes data from all weekly notifiable disease reports for the United States dating back to 1888. These data are freely available to anybody interested. I wanted to play around with the data a bit, so I registered.MeaslesMeasles a...

Read more »

President Approval Ratings from Roosevelt to Obama

March 29, 2014
By
President Approval Ratings from Roosevelt to Obama

I have been watching the awesome Netflix show “House of Cards” and been fascinated by the devious schemes that Underwood is constantly plotting. The show often mentions approval ratings and it got me to wondering what Obama’s ratings currently were, and all other past US president  for that matter. However, I didn’t have much chance

Read more »

R / Finance 2014 Open for Registration

March 29, 2014
By

The annoucement below just went to the R-SIG-Finance list. More information is as usual at the R / Finance page: Now open for registrations: R / Finance 2014: Applied Finance with R May 16 and 17, 2014 Chicago, IL, USA The reg...

Read more »

Introduction to PortfolioAnalytics

March 29, 2014
By
Introduction to PortfolioAnalytics

PortfolioAnalytics Basics This is a guest post by Ross Bennett. Ross is currently enrolled in the University of Washington Master of Science in Computational Finance & Risk Management program with an expected graduation date of December 2014. He worked on the PortfolioAnalytics...

Read more »

R/Finance 2014 Registration Open

March 29, 2014
By

As announced on the R-SIG-Finance mailing list, registration for R/Finance 2014 is now open! The conference will take place May 17 and 18 in Chicago.Building on the success of the previous conferences in 2009-2013, we expect more than 250 attendees fro...

Read more »

Theil’s Blus Residuals and R Tools for Testing and Removing Autocorrelation and Heteroscedasticity

March 28, 2014
By

Guest post by Hrishikesh (Rick) D. Vinod, Professor of Economics, Fordham University. Theil (1968) proposed a transformation of regression residuals so that they are best, unbiased, linear, scalar (BLUS). No R code is available to implement them. I am providing the detailed description of the properties of BLUS residuals to the uninitiated and code. The matrix algebra itself is...

Read more »

Alternatives to model diagnostics for statistical inference?

March 28, 2014
By
Alternatives to model diagnostics for statistical inference?

Consider the problem of making statistical inferences, as opposed to predictions. The product of statistical inference is a probabilistic statement about a population quantity, for example a 100(1-)% confidence interval for a population median. In this context, the principal reason for diagnostics is to comfort ourselves about the quality of such inferences. For example, we

Read more »