2223 search results for "regression"

Potential and Possibilities of the Programming Language R for Predictive Maintenance

April 11, 2014
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Potential and Possibilities of the Programming Language R for Predictive Maintenance

Have you ever been asked a question starting with: “Can you use R to…“, only to politely interrupt the inquisitor at this point to reply with something similar to “Yes, you can! R probably already has a package for this”. If this sounds familiar to you, you won’t be overly surprised to hear that R

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R 3.1.0 is released!

April 10, 2014
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R 3.1.0 is released!

R 3.1.0 (codename “Spring Dance“) was released today! You can get the source code from http://cran.r-project.org/src/base/R-3/R-3.1.0.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. The full list of new features and bug fixes is provided below. Upgrading to R 3.1.0 You can

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BARUG talks highlight R’s diverse applications

April 10, 2014
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BARUG talks highlight R’s diverse applications

by Joseph Rickert The seven lightning talks presented to the Bay Area useR Group on Tuesday night were not only really interesting (in some cases downright entertaining) in their own right, but they also illustrated the diversity of R applications, and the extent to which R has become embedded in the corporate world. Two presentations with a whimsical touch...

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Ensemble Packages in R

April 8, 2014
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Ensemble Packages in R

by Mike Bowles Mike Bowles is a machine learning expert and serial entrepreneur. This is the second post in what is envisioned as a four part series that began with Mike's Thumbnail History of Ensemble Models. One of the main reasons for using R is the vast array of high-quality statistical algorithms available in R. Ensemble methods provide a...

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In case you missed it: March 2014 roundup

April 7, 2014
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In case you missed them, here are some articles from March of particular interest to R users: Francis Smart offers five excellent reasons to use R, and notes that R is the top Google Search for statistical software. Revolution Analytics is offering R training for SAS users in Singapore and online. The number of R user groups worldwide continues...

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Author inflation in academic literature

April 6, 2014
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Author inflation in academic literature

There seems to be a general consensus that author lists in academic articles are growing. Wikipedia says so, and I’ve also come across a published letter and short Nature article which accept this is the case and discuss ways of … Continue reading →

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Flip the script, or, the joys of coord_flip()

April 4, 2014
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Flip the script, or, the joys of coord_flip()

Has this ever happened to you?I hate it when the labels on the x-axis overlap, but this can be hard to avoid. I can stretch the figure out, but then the data become farther apart and the space where I want to put the figure (either in a talk or a paper...

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Some R Resources for GLMs

April 3, 2014
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Some R Resources for GLMs

by Joseph Rickert Generalized Linear Models have become part of the fabric of modern statistics, and logistic regression, at least, is a “go to” tool for data scientists building classification applications. The ready availability of good GLM software and the interpretability of the results logistic regression makes it a good baseline classifier. Moreover, Paul Komarek argues that, with a...

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Inference for ARCH processes

April 2, 2014
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Inference for ARCH processes

Consider some ARCH() process, say ARCH(), where with a Gaussian (strong) white noise . > n=500 > a1=0.8 > a2=0.0 > w= 0.2 > set.seed(1) > eta=rnorm(n) > epsilon=rnorm(n) > sigma2=rep(w,n) > for(t in 3:n){ + sigma2=w+a1*epsilon^2+a2*epsilon^2 + epsilon=eta*sqrt(sigma2) + } > par(mfrow=c(1,1)) > plot(epsilon,type="l",ylim=c(min(epsilon)-.5,max(epsilon))) > lines(min(epsilon)-1+sqrt(sigma2),col="red") (the red line is the conditional variance process). > par(mfrow=c(1,2)) > acf(epsilon,lag=50,lwd=2)...

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IV Estimates via GMM with Clustering in R

April 1, 2014
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IV Estimates via GMM with Clustering in R

In econometrics, generalized method of moments (GMM) is one estimation methodology that can be used to calculate instrumental variable (IV) estimates. Performing this calculation in R, for a linear IV model, is trivial. One simply uses the gmm() function in the excellent gmm package like an lm() or ivreg() function. The gmm() function will estimate

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