1764 search results for "regression"

Export R Results Tables to Excel – Please don’t kick me out of your club

August 19, 2013
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Export R Results Tables to Excel – Please don’t kick me out of your club

This post is written as a result of finding the following exchange on one of the R mailing lists:Is-there-a-way-to-export-regression-output-to-an-excel-spreadsheetQuestion: Is there a way to export regression output to an excel spreadsheet?Translation:...

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Gaussian Processes with RStan

August 19, 2013
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Gaussian Processes with RStan

Email Previously I looked at how to simulate Gaussian processes in R, following the methods in Rasmussen and Williams. But now that Andrew Gelman et al. (of

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Question and Answer: Generating Binary and Discrete Response Data

August 19, 2013
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I was recently contacted by a reader with two very specific questions and I thought that this would be a good topic to publicity respond to. He would like to simulate his data:I have firm level data and the model is discrete choice with the main expla...

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R vs Python Speed Comparison for Bootstrapping

August 19, 2013
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R vs Python Speed Comparison for Bootstrapping

I’m interested in Python a lot, mostly because it appears to be wickedly fast. The downside is that I don’t know it nearly as well as R, so any speed gain in computation time is more than offset by Google … Continue reading →

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The Bayesian Counterpart of Pearson’s Correlation Test

August 19, 2013
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The Bayesian Counterpart of Pearson’s Correlation Test

Except for maybe the t test, a contender for the title “most used and abused statistical test” is Pearson’s correlation test. Whenever someone wants to check if two variables relate somehow it is a safe bet (at least in psychology) that the first thing to be tested is the strength of a Pearson’s correlation. Only if that doesn’t...

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Fitting a Model by Maximum Likelihood

August 18, 2013
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Fitting a Model by Maximum Likelihood

Maximum-Likelihood Estimation (MLE) is a statistical technique for estimating model parameters. It basically sets out to answer the question: what model parameters are most likely to characterise a given set of data? First you need to select a model for the data. And the model must have one or more (unknown) parameters. As the name

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How do I re-arrange??: Ordering a plot revisited

August 14, 2013
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How do I re-arrange??: Ordering a plot revisited

Back in October of last year I wrote a blog post about reordering/rearanging plots. This was, and continues to be, a frequent question on list serves and R help sites. In light of my recent studies/presenting on The Mechanics of … Continue reading →

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predictNLS (Part 1, Monte Carlo simulation): confidence intervals for ‘nls’ models

August 14, 2013
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predictNLS (Part 1, Monte Carlo simulation): confidence intervals for ‘nls’ models

Those that do a lot of nonlinear fitting with the nls function may have noticed that predict.nls does not have a way to calculate a confidence interval for the fitted value. Using confint you can obtain the error of the fit parameters, but how about the error in fitted values? ?predict.nls says: “At present se.fit

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Exposure as a possible explanatory variable

August 13, 2013
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Exposure as a possible explanatory variable

Iin insurance pricing, the exposure is usually used as an offset variable to model claims frequency. As explained many times on this blog (e.g. here), and in my notes, if we have to identical drivers, but one with an exposure of 6 months, and the other one of one year, it should be natural to assume that, on average,...

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A Stata HTML syntax highlighter in R

August 12, 2013
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So I have been having difficulty getting my Stata code to look the way I want it to look when I post it to my blog.  To alleviate this condition I have written a html encoder in R.  I don't know much about html so it is likely to be a little ...

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