1187 search results for "Latex"

Bayesian model choice for the Poisson model

February 1, 2013
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Bayesian model choice for the Poisson model

Following Arthur Charpentier‘s example, I am going to try to post occasionally on material covered during my courses, in the hope that it might be useful to my students, but also to others. In the second practical of the Bayesian Case Studies course, we looked at Bayesian model choice and basic Monte Carlo methods, looking

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Regression on categorical variables

January 30, 2013
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Regression on categorical variables

This morning, Stéphane asked me tricky question about extracting coefficients from a regression with categorical explanatory variates. More precisely, he asked me if it was possible to store the coefficients in a nice table, with information on the variable and the modality (those two information being in two different columns). Here is some code I did to produce the...

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The magic empty bracket

January 30, 2013
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The magic empty bracket

I have been working with R for some time now, but once in a while, basic functions catch my eye that I was not aware of… For some project I wanted to transform a correlation matrix into a covariance matrix. Now, since cor2cov does not exist, I thought about “reversing” the cov2cor function (stats:::cov2cor). Inside

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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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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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Regression tree using Gini’s index

January 27, 2013
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Regression tree using Gini’s index

In order to illustrate the construction of regression tree (using the CART methodology), consider the following simulated dataset, > set.seed(1) > n=200 > X1=runif(n) > X2=runif(n) > P=.8*(X1<.3)*(X2<.5)+ + .2*(X1<.3)*(X2>.5)+ + .8*(X1>.3)*(X1<.85)*(X2<.3)+ + .2*(X1>.3)*(X1<.85)*(X2>.3)+ + .8*(X1>.85)*(X2<.7)+ + .2*(X1>.85)*(X2>.7) > Y=rbinom(n,size=1,P) > B=data.frame(Y,X1,X2) with one dichotomos varible (the variable of interest, ), and two continuous ones (the explanatory ones  and ). > tail(B) Y...

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Learning R using a Chemical Reaction Engineering Book: Part 3

January 26, 2013
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Learning R using a Chemical Reaction Engineering Book: Part 3

In case you missed previous parts, the links to them are listed below. Part 1 Part 2 In this part, I tried to recreate the examples in section A.2.3 of the computational appendix in the reaction engineering book (by Rawlings and … Continue reading →

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Learning R using a Chemical Reaction Engineering Book: Part 2

January 26, 2013
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Learning R using a Chemical Reaction Engineering Book: Part 2

In case you missed part 1, you can view it here. In this part, I tried to recreate the examples in section A.2.2 of the computational appendix in the reaction engineering book by Rawlings and Ekerdt. Solving a nonlinear system of equations … Continue reading →

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Learning R using a Chemical Reaction Engineering Book: Part 1

January 25, 2013
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Learning R using a Chemical Reaction Engineering Book: Part 1

Chemical Reactor Analysis and Design Fundamentals by J.B. Rawlings and J. G. Ekerdt is a textbook for studying Chemical Reaction Engineering. The popular open source package Octave has its origins to the reaction engineering course offered by Prof. Rawlings. This book … Continue reading →

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No more ascii-art

January 24, 2013
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No more ascii-art

At least fourfive R packages will turn your regression models into pretty latex tables: texreg, xtable, apsrtable, memisc, and stargazer.  This is very nice if you happen to be a latex document or its final reader, but it’s not so great if you’re making those models to start with. What if you wanted to see

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