Posts Tagged ‘ Linear Models ’

INLA: Bayes goes to Norway

August 15, 2012
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INLA: Bayes goes to Norway

INLA is not the Norwegian answer to ABBA; that would probably be a-ha. INLA is the answer to ‘Why do I have enough time to cook a three-course meal while running MCMC analyses?”. Integrated Nested Laplace Approximations (INLA) is based … Continue reading →

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Split-plot 1: How does a linear mixed model look like?

June 24, 2012
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Split-plot 1: How does a linear mixed model look like?

I like statistics and I struggle with statistics. Often times I get frustrated when I don’t understand and I really struggled to make sense of Krushke’s Bayesian analysis of a split-plot, particularly because ‘it didn’t look like’ a split-plot to … Continue reading →

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Bivariate linear mixed models using ASReml-R with multiple cores

May 7, 2012
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Bivariate linear mixed models using ASReml-R with multiple cores

A while ago I wanted to run a quantitative genetic analysis where the performance of genotypes in each site was considered as a different trait. If you think about it, with 70 sites and thousands of genotypes one is trying … 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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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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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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Spatial correlation in designed experiments

October 20, 2011
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Spatial correlation in designed experiments

Last Wednesday I had a meeting with the folks of the New Zealand Drylands Forest Initiative in Blenheim. In addition to sitting in a conference room and having nice sandwiches we went to visit one of our progeny trials at … Continue reading →

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Large applications of linear mixed models

October 18, 2011
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Large applications of linear mixed models

In a previous post I summarily described our options for (generalized to varying degrees) linear mixed models from a frequentist point of view: nlme, lme4 and ASReml-R†, followed by a quick example for a split-plot experiment. But who is really … Continue reading →

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Linear mixed models in R

October 16, 2011
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A substantial part of my job has little to do with statistics; nevertheless, a large proportion of the statistical side of things relates to applications of linear mixed models. The bulk of my use of mixed models relates to the … Continue reading →

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