2223 search results for "regression"

Introducing parallelRandomForest: faster, leaner, parallelized

September 23, 2013
By
ffffffffffffforst

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...

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Detecting Weak Instruments in R

September 23, 2013
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Detecting Weak Instruments in R

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

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“Statistical Models with R” Course – Milano, October 24-25, 2013

September 19, 2013
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MilanoR, in collaboration with Quantide, organizes "Statistical Models with R" Course October 24-25, 2013 Course description This two-day course shows a wide variety of statistical models with R ranging from Linear Models (LM) to Generalized Linear Models (GLM) modelling, in … Continue reading →

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informative hypotheses (book review)

September 18, 2013
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informative hypotheses (book review)

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

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PirateGrunt goes to the CLRS

September 16, 2013
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PirateGrunt goes to the CLRS

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

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Forecasting with daily data

September 16, 2013
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Forecasting with daily data

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)...

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New robust statistical functions in WRS package – Guest post by Rand Wilcox

September 16, 2013
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New robust statistical functions in WRS package – Guest post by Rand Wilcox

Today a new version (0.23.1) of the WRS package (Wilcox’ Robust Statistics) has been released. This package is the companion to his rather exhaustive book on robust statistics, “Introduction to Robust Estimation and Hypothesis Testing” (Amazon Link de/us). For a fail-safe installation of the package, follow this instruction. As a guest post, Rand Wilcox describes

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BCEA in UseR!

September 13, 2013
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BCEA in UseR!

In a recent post, I had hinted at big news for BCEA $-$ I thought it was pretty much a done deal, but because it wasn't yet set in stone, I didn't want to jinx it...But now I've sorted all the details with Springer, who have asked me to write a book on the...

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Alpha Testing RevoScaleR running in Hadoop

September 13, 2013
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by Joseph Rickert At Revolution Analytics our mission is to establish R as the driver for Enterprise level computational frameworks. In part, this means that a data scientist ought to be able to develop an R based application in one context, e.g. her local PC, and then get it moving by changing horses on the fly (so to speak)...

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Direction of Change Forecasting using a Dynamic Binary Model

September 12, 2013
By
Direction of Change Forecasting using a Dynamic Binary Model

While it is generally accepted that the returns of financial assets are almost impossible to forecast with any degree of accuracy which would provide meaningful profit1 , there is evidence that the sign of the returns is much more forecastable. Theoretically, Christoffersen and Diebold (2006) have shown how the forecastability of the sign is related

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