1736 search results for "regression"

Priors

July 16, 2013
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Nick Firoozye writes: While I am absolutely sympathetic to the Bayesian agenda I am often troubled by the requirement of having priors. We must have priors on the parameter of an infinite number of model we have never seen before and I find this troubling. There is a similarly troubling problem in economics of utility The post Priors...

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Tailor Your Tables with stargazer: New Features for LaTeX and Text Output

July 15, 2013
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Tailor Your Tables with stargazer: New Features for LaTeX and Text Output

Guest post by Marek Hlavac Since its first introduction on this blog, stargazer, a package for turning R statistical output into beautiful LaTeX and ASCII text tables, has made a great deal of progress. Compared to available alternatives (such as …Read more »

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Zero to hero

July 13, 2013
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Zero to hero

Recently, I've been working on a paper, which I think is coming along nicely. The basic problem is like this: in a health economic evaluation, sometimes data are collected on a sample of individuals. Say, for example, that $n_0$ subjects are given a st...

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UseR! 2013: it’s a wrap!

July 12, 2013
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UseR! 2013: it’s a wrap!

Steve Scott (Google) presents at useR! 2013, July 12 2013 The 2013 UseR! conference has drawn to a close in Albacete, Spain. The conference organizers did a fantastic job putting together a jam-packed presentation and social program for the 350+ R users in attendance. Here are just a few of my highlights from the last couple of days: Duncan...

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rxDTree(): a new type of tree algorithm for big data

July 11, 2013
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by Joseph Rickert The rxDTree() function included in the RevoScaleR package distributed with Revolution R Enterprise is an an example of a new class of algorithms that are being developed to deal with very large data sets. Although the particulars differ, what these algorithms have in common is the use of approximations, methods of summarizing or compressing data and...

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user2013: The caret tutorial

July 9, 2013
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user2013: The caret tutorial

This afternoon I went to Max Kuhn’s tutorial on his caret package. caret stands for classification and regression (something beginning with e) trees. It provides a consistent interface to nearly 150 different models in R, in much the same way as the plyr package provides a consistent interface to the apply functions. The basic usage

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Modeling Residential Electricity Usage with R – Part 2

July 8, 2013
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Modeling Residential Electricity Usage with R – Part 2

(This article was first published on Commodity Stat Arb, and kindly contributed to R-bloggers) I can’t believe it has been nearly 6 months since I last posted.  Given the sustained heat it seemed like a good idea to finish off this subject. As hinted at in my last post, temperature is the missing variable to make sense of Residential...

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Veterinary Epidemiologic Research: Modelling Survival Data – Parametric and Frailty Models

July 5, 2013
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Veterinary Epidemiologic Research: Modelling Survival Data – Parametric and Frailty Models

Last post on modelling survival data from Veterinary Epidemiologic Research: parametric analyses. The Cox proportional hazards model described in the last post make no assumption about the shape of the baseline hazard, which is an advantage if you have no idea about what that shape might be. With a parametric survival model, the survival time

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Allocation Models With Bounded Dependent Variables

July 5, 2013
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Allocation Models With Bounded Dependent Variables

(This article was first published on Econometrics Beat: Dave Giles' Blog, and kindly contributed to R-bloggers) My post yesterday, on Allocation Models, drew a comment to the effect that in such models the dependent variables take values that must to be non-negative fractions. Well, as I responded, that’s true sometimes (e.g., in the case of market shares); but not in...

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Using neural networks for credit scoring: a simple example

July 4, 2013
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Using neural networks for credit scoring: a simple example

Credit scoring is the practice of analysing a persons background and credit application in order to assess the creditworthiness of the person. One can take numerous approaches on analysing this creditworthiness. In the end it basically comes down to first selecting the correct independent variables (e.g. income, age, gender) that lead to a given level of creditworthiness. In...

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