Center for Theoretical Study, Prague: more intense than ivy league

By | October 8, 2014

I have recently been lucky to relocate from Yale to Center for Theoretical Study in Prague, Czech Republic. The institute brings together philosophers, mathematicians, physicists, sociologists, economists, biologists and others; it is similar to Santa Fe Institute or Princeton Institute for Advanced Study, and its aim is to stimulate interdisciplinary approaches to science, encouraging new… Read More »

Species Distribution Models on the right track. Finally.

By | September 2, 2014

Species Distribution Models (SDM) a.k.a. Niche Models have always been a busy pile of confusion, ideology and misguided practices, with the real mess being the “presence only” SDMs. Interestingly, when you go to conservation or biogeography symposiums, you can hear the established SDM gurus starting their talks with: “During the last ten years SDMs have… Read More »

Is my brilliant idea any good? I am not sure, so I've pre-printed it on PeerJ

By | July 24, 2014

As a scientist, what should I do when I encounter a seemingly fundamental problem that also seems strangely unfamiliar? Is it unfamiliar because I am up to something really new, or am I re-discovering something that has been around for centuries, and I have just missed it? This is a short story about an exploration… Read More »

Do 'macrosystems ecologists' know about macroecology?

By | February 18, 2014

Paper by Levy et al. in Frontiers in Ecology and the Environment announces emergence of a new ecological discipline called macrosystems ecology (MSE). The authors define MSE like this: MSE studies explore how broad-scale variation in fine-scale characteristics – such as organismal behavior and fitness, nutrient transformations, and water-use efficiency – relate to broad-scale spatial… Read More »

Spatial autocorrelation of errors in JAGS

By | February 10, 2014

In the core of kriging, Generalized-Least Squares (GLS) and geostatistics lies the multivariate normal (MVN) distribution – a generalization of normal distribution to two or more dimensions, with the option of having non-independent variances (i.e. autocorrelation). In this post I will show: (i) how to use exponential decay and the multivariate normal distribution to simulate… Read More »

Bayesian Biostatistics 2014

By | February 2, 2014

This post contains materials for Bayesian stats course that I taught between 2-4 Feb 2014 at Faculty of Science, Charles University, Prague, Czech Republic. There were around 40 participants. The complete materials and their source codes (Markdown and R) are on a GitHub repository. The lectures can also be accessed directly as follows (I recommend… Read More »

Poisson regression fitted by glm(), maximum likelihood, and MCMC

By | October 30, 2013

The goal of this post is to demonstrate how a simple statistical model (Poisson log-linear regression) can be fitted using three different approaches. I want to demonstrate that both frequentists and Bayesians use the same models, and that it is the fitting procedure and the inference that differs. This is also for those who understand… Read More »

Do simple models lead to generality in ecology? Opinion of a simpleton

By | September 25, 2013

Evans et al. have a paper in Trends in Ecology and Evolution with this abstract: Modellers of biological, ecological, and environmental systems cannot take for granted the maxim ‘simple means general means good’. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of… Read More »

The joy and martyrdom of trying to be a Bayesian

By | August 30, 2013

Some of my fellow scientists have it easy. They use predefined methods like linear regression and ANOVA to test simple hypotheses; they live in the innocent world of bivariate plots and lm(). Sometimes they notice that the data have odd histograms and they use glm(). The more educated ones use generalized linear mixed effect models.… Read More »

The effect of ski-pistes on butterflies

By | July 19, 2013

I have a weak spot for butterflies, and I love skiing. Every time I go up a ski lift I wonder how such a major landscape modification (ski pistes or ski slopes) affects nature. I have always had the impression that clear-cutting long and wide strips in mountain forests is not necessarily a bad thing.… Read More »

Is basic science infantile?

By | July 15, 2013

Time has an article on what happens when creative thinkers get the opportunity to set their minds free. The article begins at the Institute for Advanced Study in Princeton and ends up as an essay on the old "rivalry" between basic and applied science. Opinions of two of the Institute's researchers are contrasted. Norwegian mathematician… Read More »

Seeing Pierre Legendre

By | June 10, 2013

As suggested by his name, the guy is a legend. One of the most cited authors in ecology, I have him in (almost) the same league with James H. Brown, sir Robert M. May or Stephen P. Hubbell. Legendre is not famous for creating a revolutionary ecological theory and he does not stand out as… Read More »

Spatial correlograms in R: a mini overview

By | May 21, 2013

Spatial correlograms are great to examine patterns of spatial autocorrelation in your data or model residuals. They show how correlated are pairs of spatial observations when you increase the distance (lag) between them - they are plots of some index of autocorrelation (Moran's I or Geary's c) against distance. Although correlograms are not as fundamental… Read More »

Beware: 2 is not always 2 in R

By | May 14, 2013

This post is minimalistic. Consider this: Now let's have look at what's inside x: But is it really true? Here you go. A colleague of mine was once ruined by this for an entire day before we realized what was going on. So, how to find out what REALLY is the value of x? Try:

Category: R

AIC & BIC vs. Crossvalidation

By | May 5, 2013

Model selection is a process of seeking the model in a set of candidate models that gives the best balance between model fit and complexity (Burnham & Anderson 2002). I have always used AIC for that. But you can also do that by crossvalidation. Specifically, Stone (1977) showed that the AIC and leave-one out crossvalidation… Read More »

Where do birders go?

By | April 30, 2013

Yesterday during our spatial ecology class we explored geographic patterns of localities which bird observers like to go to in the US. Here is the map which I produced - it is based on eBird 3.0 reference dataset and it shows density of all birding checklist submitted between 2000 and 2012, at 10 x 10… Read More »

On ensemble forecasting

By | April 27, 2013

Yesterday, professor Ronald Smith gave a talk at Yale about how to predict future climate. One of his central subjects was ensemble forecasting. Here I give it a bit of a dissection. Climatologists and ecologists do "predictive models". Once they have the model, they use it to predict the future, e.g.: How will global temperature… Read More »

Direct support for hypotheses is finding its way to high-profile journals

By | April 23, 2013

In this week's Nature paper, Tingley & Huybers report that recent temperature extremes at high northern latitudes are unprecedented in the past 600 years. Besides the scientific relevance (which I do not discuss here) it has one remarkable methodological aspect: it uses hierarchical Bayesian modelling. Moreover, what is really exciting is the way the authors… Read More »

Not all proportion data are binomial outcomes

By | March 24, 2013

It really is trivial. Not every proportion is frequency. There are things that have values  bounded between 0 and 1 and yet they are neither probabilities, nor frequencies. Why do I even bother to write this? Because some kinds of proportions should be treated as unbounded continuous variables, and should be analyzed using appropriate statistical… Read More »

Predictors, responses and residuals: What really needs to be normally distributed?

By | February 18, 2013

Introduction Many scientists are concerned about normality or non-normality of variables in statistical analyses. The following and similar sentiments are often expressed, published or taught: "If you want to do statistics, then everything needs to be normally distributed." "We normalized our data in order to meet the assumption of normality." "We log-transformed our data as… Read More »