Blog Archives

On the (statistical) road, workshops and R

December 3, 2011
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On the (statistical) road, workshops and R

Things have been a bit quiet at Quantum Forest during the last ten days. Last Monday (Sunday for most readers) I flew to Australia to attend a couple of one-day workshops; one on spatial analysis (in Sydney) and another one … Continue reading →

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If you are writing a book on Bayesian statistics

November 23, 2011
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This post is somewhat marginal to R in that there are several statistical systems that could be used to tackle the problem. Bayesian statistics is one of those topics that I would like to understand better, much better, in fact. … Continue reading →

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Do we need to deal with ‘big data’ in R?

November 22, 2011
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Do we need to deal with ‘big data’ in R?

David Smith at the Revolutions blog posted a nice presentation on “big data” (oh, how I dislike that term). It is a nice piece of work and the Revolution guys manage to process a large amount of records, starting with … Continue reading →

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Surviving a binomial mixed model

November 11, 2011
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Surviving a binomial mixed model

A few years ago we had this really cool idea: we had to establish a trial to understand wood quality in context. Sort of following the saying “we don’t know who discovered water, but we are sure that it wasn’t … Continue reading →

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Coming out of the (Bayesian) closet: multivariate version

November 7, 2011
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Coming out of the (Bayesian) closet: multivariate version

This week I’m facing my—and many other lecturers’—least favorite part of teaching: grading exams. In a supreme act of procrastination I will continue the previous post, and the antepenultimate one, showing the code for a bivariate analysis of a randomized … Continue reading →

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Teaching with R: the tools

November 1, 2011
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I bought an Android phone, nothing fancy just my first foray in the smartphone world, which is a big change coming from the dumb phone world(*). Everything is different and I am back at being a newbie; this is what … Continue reading →

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Multivariate linear mixed models: livin’ la vida loca

October 31, 2011
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Multivariate linear mixed models: livin’ la vida loca

I swear there was a point in writing an introduction to covariance structures: now we can start joining all sort of analyses using very similar notation. In a previous post I described simple (even simplistic) models for a single response … Continue reading →

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Covariance structures

October 26, 2011
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Covariance structures

In most mixed linear model packages (e.g. asreml, lme4, nlme, etc) one needs to specify only the model equation (the bit that looks like y ~ factors...) when fitting simple models. We explicitly say nothing about the covariances that complete … Continue reading →

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Longitudinal analysis: autocorrelation makes a difference

October 25, 2011
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Longitudinal analysis: autocorrelation makes a difference

Back to posting after a long weekend and more than enough rugby coverage to last a few years. Anyway, back to linear models, where we usually assume normality, independence and homogeneous variances. In most statistics courses we live in a … Continue reading →

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Teaching with R: the switch

October 21, 2011
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There are several blog posts, websites (and even books) explaining the transition from using another statistical system (e.g. SAS, SPSS, Stata, etc) to relying on R. Most of that material treats the topic from the point of view of i- … Continue reading →

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