Blog Archives

Tall big data, wide big data

December 12, 2011
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After attending two one-day workshops last week I spent most days paying attention to (well, at least listening to) presentations in this biostatistics conference. Most presenters were R users—although Genstat, Matlab and SAS fans were also present and not one … Continue reading →

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R, academia and the democratization of statistics

December 12, 2011
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R, academia and the democratization of statistics

I am not a statistician but I use statistics, teach some statistics and write about applications of statistics in biological problems. Last week I was in this biostatistics conference, talking with a Ph.D. student who was surprised about this situation … Continue reading →

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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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