# 2067 search results for "Regression"

## user2013: The caret tutorial

July 9, 2013
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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

## Modeling Residential Electricity Usage with R – Part 2

July 8, 2013
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(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...

## 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

## Allocation Models With Bounded Dependent Variables

July 5, 2013
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(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...

## Using neural networks for credit scoring: a simple example

July 4, 2013
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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...

## My take on the USA versus Western Europe comparison of GM corn

July 4, 2013
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A few days ago I came across Jack Heinemann and collaborators’ article (Sustainability and innovation in staple crop production in the US Midwest, Open Access) comparing the agricultural sectors of USA and Western Europe‡. While the article is titled around the word sustainability, the main comparison stems from the use of Genetically Modified crops in

## Fun with random effects in loss reserving

July 3, 2013
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For some time now, I’ve advocated for the view that non-life loss reserving constitutes a categorized linear regression. I’ll emphasize that the idea of a linear regression isn’t remotely novel. Further, the categorization is the de facto approach. I’m merely recognizing it and suggesting instances where a decision may be made about the optimality of

## The hat trick

July 3, 2013
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In his book Quantum Computing Since Democritus, Scott Aaronson poses the following question: Suppose that you’re at a party where every guest is given a hat as they walk in. Each hat has either a pineapple or a watermelon on top, picked at random with equal probability. The guests don’t get to see the fruit

## In case you missed it: June 2013 Roundup

July 3, 2013
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In case you missed them, here are some articles from June of particular interest to R users: You can create a Word document from a template and an R script with the R2DOCX package. Joe Rickert reviews books and other resources for learning about time series analysis in R. Timely Portfolio covers 15 years of history of time series...

## Predictive analysis on Web Analytics tool data

July 3, 2013
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In our previous webinar, we discussed on predictive analytics and basic things to perform predictive analysis. We also discussed on an eCommerce problem and how it can be solved using predictive analysis. In this post, I will explain R script that I used to perform predictive analysis during webinar. Before I explain about R script,