The free statistical programming language R becomes more and more popular, even in German speaking areas. This happens for various reasons. Besides from its performance, its quality and its open source character, R scores with its various possibilities for integration. Beyond that R offers a multitude of possibilities in the field of multivariate analysis methods.
A series of tutorials, in R, by Anthony Damico. As claimed on http://twotorials.com/, “how to do stuff in r. two minutes or less, for those of us who prefer to learn by watching and listening“. So far, 000 what is r? the lingua statistica, s’il vous plaît 001 how to download and install r 002 simple shortcuts for the windows r...
MRMR version 0.1.3 is now available on CRAN. This is (almost) the same version that was discussed at the CLRS two weeks ago. MRMR – Multivariate Regression Models for Reserving- is a tool for non-life actuaries to estimate liability reserves. The emphasis is on exploratory data analysis, visualization and model diagnostics. At present, the framework
Dr. Hadley Wickham is the Chief Scientist of RStudio and Assistant Professor
of Statistics at Rice University. He is the developer of the famous R package ggplot2
for data visualization and the author of many other widely used packages like plyr
and reshape2. On Sep 13, 2013 he gave a talk at Department of Statistics,
Purdue University, and later I...
R 3.0.2 (codename “Frisbee Sailing”) was released yesterday. The full list of new features and bug fixes is provided below. Also, RStudio v0.98 (in a “secret” preview) was announced two days ago with MANY new features, including: Amazing new debugging …Read more »
Together with other members of Andreas Beyer's research group, I participated in the DREAM 8 toxicogenetics challenge. While the jury is still out on the results, I want to introduce my improvement of the R randomForest package, namely parall...
Any instrumental variables (IV) estimator relies on two key assumptions in order to identify causal effects: That the excluded instrument or instruments only effect the dependent variable through their effect on the endogenous explanatory variable or variables (the exclusion restriction), That the correlation between the excluded instruments and the endogenous explanatory variables is strong enough
The title of this book Informative Hypotheses somehow put me off from the start: the author, Hebert Hoijtink, seems to distinguish between informative and uninformative (deformative? disinformative?) hypotheses. Namely, something like H0: μ1=μ2=μ3=μ4 is “very informative” and the alternative Ha is completely uninformative, while the “alternative null” H1: μ1<μ2=μ3<μ4 is informative. (Hence the < signs on
Yesterday, I had the great pleasure to speak about using R for loss reserving at the Casualty Loss Reserving Seminar in Boston. My time was spent talking about MRMR, an R package that I’ve created. Version 0.1.2 is now on CRAN, but as there are a couple of bugs, I’d suggest waiting until version 0.1.3
I’ve had several emails recently asking how to forecast daily data in R. Unless the time series is very long, the simplest approach is to simply set the frequency attribute to 7. y <- ts(x, frequency=7) Then any of the usual time series forecasting methods should produce reasonable forecasts. For example library(forecast) fit <- ets(y) fc <- forecast(fit) plot(fc)...