1663 search results for "Regression"

Reserving based on log-incremental payments in R, part II

January 15, 2013
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Reserving based on log-incremental payments in R, part II

Following on from last week's post I will continue to go through the paper Regression models based on log-incremental payments by Stavros Christofides . In the previous post I introduced the model from the first 15 pages up to section F. Today I will progress with sections G to K which illustrate the model with a...

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{stargazer} package for beautiful LaTeX tables from R statistical models output

January 14, 2013
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{stargazer} package for beautiful LaTeX tables from R statistical models output

stargazer is a new R package that creates LaTeX code for well-formatted regression tables, with multiple models side-by-side, as well as for summary statistics tables. Its latest version, released in early January 2013, can also output the content of data …Read more »

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analyze the health and retirement study (hrs) with r

January 14, 2013
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the hrs is the one and only longitudinal survey of american seniors.  with a panel starting its third decade, the current pool of respondents includes older folks who have been interviewed every two years as far back as 1992.  unlike cross-se...

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The Cluster Bootstrap

January 12, 2013
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The Cluster Bootstrap

Adjusting standard errors for clustering can be a very important part of any statistical analysis. For example, duplicating a data set will reduce the standard errors dramatically despite there being no new information. I have previously dealt with this topic with reference to the linear regression model. However, in many cases one would like to

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PART – A Rule-Learning Algorithm

January 11, 2013
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PART – A Rule-Learning Algorithm

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Formulae in R: ANOVA and other models, mixed and fixed

January 10, 2013
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R’s formula interface is sweet but sometimes confusing. ANOVA is seldom sweet and almost always confusing. And random (a.k.a. mixed) versus fixed effects decisions seem to hurt peoples’ heads too. So, let’s dive into the intersection of these three. I’m aware that there are lots of packages for running ANOVA models that make things nicer

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R for actuarial science

January 10, 2013
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R for actuarial science

As mentioned in the Appendix of Modern Actuarial Risk Theory, “R (and S) is the ‘lingua franca’ of data analysis and statistical computing, used in academia, climate research, computer science, bioinformatics, pharmaceutical industry, customer analytics, data mining, finance and by some insurers. Apart from being stable, fast, always up-to-date and very versatile, the chief advantage of R is that...

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Elements of Statistical Learning: free book download

January 9, 2013
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The go-to bible for this data scientist and many others is The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Each of the authors is an expert in machine learning / prediction, and in some cases invented the techniques we turn to today to make sense of big data: ensemble...

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Reserving based on log-incremental payments in R, part I

January 8, 2013
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A recent post on the PirateGrunt blog on claims reserving inspired me to look into the paper Regression models based on log-incremental payments by Stavros Christofides , published as part of the Claims Reserving Manual (Version 2) of the Institute of Actuaries.The paper is available together with a spread sheet model, illustrating the calculations. It...

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Breaking the rules with spatial correlation

January 7, 2013
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Breaking the rules with spatial correlation

Students in any basic statistics class are taught linear regression, which is one of the simplest forms of a statistical model. The basic idea is that a ‘response’ variable can be mathematically related to one or any number of ‘explanatory’ variables through a linear equation and a normally distributed error term. With any statistical tool,

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