1552 search results for "regression"

Amazing fMRI plots for everybody!

September 5, 2012
By
Amazing fMRI plots for everybody!

Dear valued customer, it is a well-known scientific truth that research results which are accompanied by a fancy, colorful fMRI scan, are perceived as more believable and more persuasive than simple bar graphs or text results (McCabe & Castel, 2007; Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). Readers even agree more with fictitious and unsubstantiated

Read more »

BMR: Bayesian Macroeconometrics in R

September 4, 2012
By
BMR: Bayesian Macroeconometrics in R

The recently released BMR package, short for Bayesian Macroeconometrics with R, provides a comprehensive set of powerful routines that estimate Bayesian Vector Autoregression (VAR) and Dynamic Stochastic General Equilibrium (DSGE) models in R. The procedure of estimating both Bayesian VAR and DSGE models can represent a great computational burden. However, BMR removes a lot of

Read more »

Descriptive statistics of some Agile feature characteristics

September 2, 2012
By
Descriptive statistics of some Agile feature characteristics

The purpose of software engineering research is to figure out how software development works so that the software industry can improve its quality/timeliness (i.e., lower costs and improved customer satisfaction). Research is hampered by the fact that companies are not usually willing to make public good quality data about the details of their software development

Read more »

New Attribution Functions for PortfolioAnalytics

September 1, 2012
By
New Attribution Functions for PortfolioAnalytics

Another Google Summer of Code (GSoC) project this summer focused on creating functions for doing returns-based performance attribution. I’ve always been a little puzzled about why this functionality wasn’t covered already, but I think that most analysts do this kind of work in Excel. That, of course, has its own perils. But beyond the workflow

Read more »

RStan: Fast, multilevel Bayesian modeling in R

August 31, 2012
By

For the last decade or so, the go-to software for Bayesian statisticians has been BUGS (and later the open-source incarnation, OpenBugs, or JAGS). BUGS is used for multi-level modeling: using a specialized notation, you can define random variables of various distributions, set Bayesian priors for their parameters, and create the network of relationships that describe how the random variables...

Read more »

Another bunch of R (and JAGS) scripts

August 31, 2012
By
Another bunch of R (and JAGS) scripts

Probably sooner than I expected, I have managed to also upload the codes for the examples in Chapter 5 of the book, which deals with doing Bayesian health economic evaluations. Basically, there are 3 examples, which sort of represent the main clas...

Read more »

PCA or Polluting your Clever Analysis

August 31, 2012
By
PCA or Polluting your Clever Analysis

When I learned about principal component analysis (PCA), I thought it would be really useful in big data analysis, but that's not true if you want to do prediction. I tried PCA in my first competition at kaggle, but it delivered bad results. This post illustrates how PCA can pollute good predictors.When I started examining this problem,...

Read more »

Processing Data from a Statistica Worksheet Using R

August 29, 2012
By
Processing Data from a Statistica Worksheet Using R

Context: I work with data from non-profit organizations, and so a big concern in many of my analyses is if and how much people are donating from one year to the next.  One of the  things I normally like to do … Continue reading →

Read more »

Integrating R into a SAS shop

August 29, 2012
By

I work in an environment dominated by SAS, and I am looking to integrate R into our environment. Why would I want to do such a thing? First, I do not want to get rid of SAS. That would not only take away most of our investment in SAS training and hiring good quality SAS programmers, but...

Read more »

Facts About R Packages (1)

August 29, 2012
By

R Packages growth Curve Why R is so popular? There are a lot of reasons, such as: easy to learn and convenient to use, active community, open source, etc. Another important reason is the numerous contributed packages. Up to yesterday, there are 4033 R...

Read more »