1554 search results for "Regression"

Level fit summaries can be tricky in R

October 1, 2012
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Level fit summaries can be tricky in R

Model level fit summaries can be tricky in R. A quick read of model fit summary data for factor levels can be misleading. We describe the issue and demonstrate techniques for dealing with them.When modeling you often encounter what are commonly called categorical variables, which are called factors in R. Possible values of categorical variables Related posts:

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Rcpp 0.9.14

October 1, 2012
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Another release of Rcpp has just appeared on CRAN and was just uploaded to Debian. It addresses yet another issue we had on OS X and should hopefully put the build issues to rest. Three new (vectorized) sugar functions were added, along with some ne...

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Football, an ordinal model

September 30, 2012
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Football, an ordinal model

On September 19th, flo2speak remarked under a post that his/her experience is that ordinal models had better performance. That seems reason enough to try, so there we are. In examining this type of model it is found that more complex models can be...

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The simplest Species Distribution Model in OpenBUGS & R

September 27, 2012
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This post demonstrates the simplest Species Distribution Model based on logistic regression for presence/absence data. I heavily simplified the example from Kéry (2010): Introduction to WinBUGS for Ecologists, Chapter 20.Read more →

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structure and uncertainty, Bristol, Sept. 26

September 26, 2012
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structure and uncertainty, Bristol, Sept. 26

Another day full of interesting and challenging—in the sense they generated new questions for me—talks at the SuSTain workshop. After another (dry and fast) run around the Downs; Leo Held started the talks with one of my favourite topics, namely the theory of g-priors in generalized linear models. He did bring a new perspective on

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Using R in production: industry experts share their experiences

September 26, 2012
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I had a great time yesterday moderating the "R in Action" panel discussion at the DataWeek conference in San Francisco. Each of the panelists represented a company that is actively using R and/or Revolution R Enterprise. Here (from memory, since I couldn't take notes) are some the things they shared: Jesse Bridgewater from eBay talked about how R is...

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Predict Bounce Rate based on Page Load Time in Google Analytics

September 26, 2012
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Predict Bounce Rate based on Page Load Time in Google Analytics

Welcome to the second part. In the last blog post on Linear Regression with R, we have discussed about what is regression? and how it is used ? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict bounce rate as function

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Specifying Variables in R

September 25, 2012
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Specifying Variables in R

R has several ways to specify which variables to use in an analysis. Some of the most frustrating errors can result from not understanding the order in which R searches for variables. This post demonstrates that order, hopefully smoothing your … Continue reading →

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From continuous to categorical

September 24, 2012
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From continuous to categorical

During data analysis, it is often super useful to turn continuous variables into categorical ones.  In Stata you would do something like this:gen catvar=0replace catvar=1 if contvar>0 & contvar<=3replace catvar=2 if contvar>3 & co...

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The fear-index: is the VIX efficient to be warned about high volatility? (Finance & Systematic Processus)

September 24, 2012
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The fear-index: is the VIX efficient to be warned about high volatility?   (Finance & Systematic Processus)