Blog Archives

Generating your own normal distribution table

October 15, 2013
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Generating your own normal distribution table

It might sounds incredibly old fashion, but for my the exam for the ACT2121 probability course (to prepare for the exam P of the Society of Actuaries), I will provide a standard normal distribution table. The problem is that it is never the one we’re looking for (sometimes it is the survival function, sometimes it is the cumulative distribution function,...

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Please, never use my codes without checking twice (at least)!

October 9, 2013
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Please, never use my codes without checking twice (at least)!

I wanted to get back on some interesting experience, following a discussion I had with Carlos after my class, this morning. Let me simplify the problem, and change also the dataset. Consider the following dataset > db = read.table("http://freakonometrics.free.fr/db2.txt",header=TRUE,sep=";") Let me change also one little thing (in the course, we use the age of people as explanatory variables, so...

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Some heuristics about spline smoothing

October 8, 2013
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Some heuristics about spline smoothing

Let us continue our discussion on smoothing techniques in regression. Assume that . where is some unkown function, but assumed to be sufficently smooth. For instance, assume that  is continuous, that exists, and is continuous, that  exists and is also continuous, etc. If  is smooth enough, Taylor’s expansion can be used. Hence, for which can also be writen as for...

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Some heuristics about local regression and kernel smoothing

October 8, 2013
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Some heuristics about local regression and kernel smoothing

In a standard linear model, we assume that . Alternatives can be considered, when the linear assumption is too strong. Polynomial regression A natural extension might be to assume some polynomial function, Again, in the standard linear model approach (with a conditional normal distribution using the GLM terminology), parameters can be obtained using least squares, where a regression of...

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Regression on variables, or on categories?

September 30, 2013
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I admit it, the title sounds weird. The problem I want to address this evening is related to the use of the stepwise procedure on a regression model, and to discuss the use of categorical variables (and possible misinterpreations). Consider the following dataset > db = read.table("http://freakonometrics.free.fr/db2.txt",header=TRUE,sep=";") First, let us change the reference in our categorical variable  (just to...

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ROC curves and classification

September 30, 2013
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ROC curves and classification

To get back to a question asked after the last course (still on non-life insurance), I will spend some time to discuss ROC curve construction, and interpretation. Consider the dataset we’ve been using last week, > db = read.table("http://freakonometrics.free.fr/db.txt",header=TRUE,sep=";") > attach(db) The first step is to get a model. For instance, a logistic regression, where some factors were merged...

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Nice tutorials to discover R

September 28, 2013
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A series of tutorials, in R, by Anthony Damico. As claimed on http://twotorials.com/, “how to do stuff in r. two minutes or less, for those of us who prefer to learn by watching and listening“. So far, 000 what is r? the lingua statistica, s’il vous plaît 001 how to download and install r 002 simple shortcuts for the windows r...

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Logistic regression and categorical covariates

September 26, 2013
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Logistic regression and categorical covariates

A short post to get back – for my nonlife insurance course – on the interpretation of the output of a regression when there is a categorical covariate. Consider the following dataset > db = read.table("http://freakonometrics.free.fr/db.txt",header=TRUE,sep=";") > tail(db) Y X1 X2 X3 995 1 4.801836 20.82947 A 996 1 9.867854 24.39920 C 997 1 5.390730 21.25119 D 998 1...

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Monty Hall (oh no, not again)

September 13, 2013
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Monty Hall (oh no, not again)

Quite frequently, someone on the internet discovers the Monty Hall paradox, and become so enthusiastic that it becomes urgent to publish an article – or a post – about it. The latest example can be http://www.bbc.co.uk/news/magazine-24045598. I won’t blame them, I did the same a few years ago (see http://freakonometrics.hypotheses.org/776, or http://freakonometrics.hypotheses.org/775, in French). My point today is that the...

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Non-observable vs. observable heterogeneity factor

September 11, 2013
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Non-observable vs. observable heterogeneity factor

This morning, in the ACT2040 class (on non-life insurance), we’ve discussed the difference between observable and non-observable heterogeneity in ratemaking (from an economic perspective). To illustrate that point (we will spend more time, later on, discussing observable and non-observable risk factors), we looked at the following simple example. Let  denote the height of a person. Consider the following dataset >...

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