## An R package for Smith-Wilson yield curves

## Oracle R Connector for Hadoop 2.1.0 released

(This article was first published on Oracle R Enterprise, and kindly contributed to R-bloggers) Oracle R Connector for Hadoop (ORCH), a collection of R packages that enables Big Data analytics using HDFS, Hive, and Oracle Database from a local R environment, continues to make advancements. ORCH 2.1.0 is now available, providing a flexible framework while remarkably improving performance and...

## Top 100 R packages for 2013 (Jan-May)!

(This article was first published on R-statistics blog » RR-statistics blog, and kindly contributed to R-bloggers) What are the top 100 (most downloaded) R packages in 2013? Thanks to the recent release of RStudio of their “0-cloud” CRAN log files (but without including downloads from the primary CRAN mirror or any of the 88 other CRAN mirrors), we can now answer this question...

## Data imputation I

I recently entered kaggle titanic learning competition for fun and to see where my out of the box utilization of random forest would rank me (303 out of 5,882). It was interesting to see that much of the scoring differentiation came from score imputation, that is filling missing values based on other data. For example, we might have

## Using Quandl in R

Image by Jan Zander Our mantra here at Quandl is making data easy to find and easy to use. Following that goal we (and subsequently the community) have created packages that integrate Quandl’s API into a number of software platforms. Today we’ll take a look at R. R is a free statistical computing language created

## Sobol Sensitivity Analysis

Sensitivity analysis is the task of evaluating the sensitivity of a model output Y to input variables (X1,…,Xp). Quite often, it is assumed that this output is related to the input through a known function f :Y= f(X1,…,Xp). Sobol indices are generalizing the coefficient of the coefficient of determination in regression. The ith first order indice is the proportion of...

## At what sample size do correlations stabilize?

Maybe you have encountered this situation: you run a large-scale study over the internet, and out of curiosity, you frequently check the correlation between two variables. My experience with this practice is usually frustrating, as in small sample sizes (and we will see what “small” means in this context) correlations go up and down, change sign,

## The Frisch–Waugh–Lovell Theorem for Both OLS and 2SLS

The Frisch–Waugh–Lovell (FWL) theorem is of great practical importance for econometrics. FWL establishes that it is possible to re-specify a linear regression model in terms of orthogonal complements. In other words, it permits econometricians to partial out right-hand-side, or control, variables. This is useful in a variety of settings. For example, there may be cases

## Veterinary Epidemiologic Research: Modelling Survival Data – Semi-Parametric Analyses

Next on modelling survival data from Veterinary Epidemiologic Research: semi-parametric analyses. With non-parametric analyses, we could only evaluate the effect one or a small number of variables. To evaluate multiple explanatory variables, we analyze data with a proportional hazards model, the Cox regression. The functional form of the baseline hazard is not specified, which make