Monthly Archives: January 2013

Getting Started with F1 Betting Data

January 28, 2013
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Getting Started with F1 Betting Data

As part of my “learn about Formula One Stats” journey, one of the things I wanted to explore was how F1 betting odds change over the course of a race weekend, along with how well they predict race weekend outcomes. Courtesy of @flutterF1, I managed to get a peek of some betting data from one

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The "golden age" of a football player

January 28, 2013
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The "golden age" of a football player

It's been some time since my last post on football. And we're talking about european soccer here. So I finally managed to write some functions which allow me to extract player stats from www.transfermarkt.de. The site tracks lots of stats in the world of soccer. For each player, there is information about the dominant foot, height, age, the estimated...

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The law of small numbers

January 28, 2013
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The law of small numbers

In insurance, the law of large numbers (named loi des grands nombres initially by Siméon Poisson, see e.g. http://en.wikipedia.org/…) is usually mentioned to legitimate large portfolios, because of pooling and diversification: the larger the pool, the more ‘predictable’ the losses will be (in a given period). Of course, under standard statistical assumption, namely finite expected value, and independence (see http://freakonometrics.blog.free.fr/…....

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Evolution of a logistic regression

January 28, 2013
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Evolution of a logistic regression

In my last post I showed how one can easily summarize the outcome of a logistic regression. Here I want to show how this really depends on the data-points that are used to estimate the model. Taking a cue from the evolution of a correlation I have plotted the estimated Odds Ratios (ORs) depending on

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analyze the survey of consumer finances (scf) with r

January 28, 2013
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the survey of consumer finances (scf) tracks the wealth of american families.  every three years, more than five thousand households answer a battery of questions about income, net worth, credit card debt, pensions, mortgages, even the lease on th...

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My template for controlling publication quality figures

January 28, 2013
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My template for controlling publication quality figures

The following is a template that I usually start with when producing figures for publication. It allows me to control:The overall size of the figure (in inches) (WIDTH, HEIGHT)The layout of figure subplots (using the layout() function) (LO)The resoluti...

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The components garch model in the rugarch package

January 28, 2013
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The components garch model in the rugarch package

How to fit and use the components model. Previously Related posts are: A practical introduction to garch modeling Variability of garch estimates garch estimation on impossibly long series Variance targeting in garch estimation The model The components model (created by Engle and Lee) generally works better than the more common garch(1,1) model.  Some hints about … Continue reading...

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My template for controlling publication quality figures

January 28, 2013
By
My template for controlling publication quality figures

The following is a template that I usually start with when producing figures for publication. It allows me to control:The overall size of the figure (in inches) (WIDTH, HEIGHT)The layout of figure subplots (using the layout() function) (LO)The resolution of the figure (for a .png file) (RESO)I define the overall dimensions of...

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I thought R was a letter…intro/installation

January 27, 2013
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I thought R was a letter…intro/installation

I will make a confession. This past summer, I didn’t spend my spare time watching relentlessly addicting TV shows nor clubbing in San Francisco. Instead, I checked out figures. No, not the sort of figures you’re probably thinking about. The ones that are included in research papers and have the potential to be beautiful works of

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European Fishing

January 27, 2013
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European Fishing

I am playing around with Eurostat data and ggplot2 a bit more. As I progress it seems the plotting gets more easy, the data pre-processing a bit more simple and the surprises on the data stay.Eurostat dataThe data used are fish_fleet (number of ships) and fish_pr (production=catch+aquaculture). After a bit of year selection, 1992 and later, I decided to...

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