Several readers, upon seeing the risk and return ratio along with other statistics in the previous post stated that the … Continue reading →

In the first part on visualizing (generalized) linear mixed effects models, I showed examples of the new functions in the sjPlot package to visualize fixed and random effects (estimates and odds ratios) of (g)lmer results. Meanwhile, I added further features to the functions, which I like to introduce here. This posting is based on the

REDDITORS’ BEFORE AND AFTER MEASUREMENTS ANALYZED Click to enlarge How many pounds do you need to lose in order to reduce your waistline by one inch? How many kilos do you need to lose to reduce your waistline by one centimeter? We wanted to find out. We were having trouble finding published data (though we The post

Occupancy modeling is possible in Stan as shown here, despite the lack of support for integer parameters. In many Bayesian applications of occupancy modeling, the true occupancy states (0 or 1) are directly modeled, but this can be avoided by marginalizing out the true occupancy state. The Stan manual (pg. 96) gives an example of this kind...

Making a slight digression from last month’s Probable Points and Credible Intervals here is how to summarize a 2D posterior density using a highest density ellipse. This is a straight forward extension of the highest density interval to the situation where you have a two-dimensional posterior (say, represented as a two column matrix of samples) and you want...

Why open data growth At rOpenSci we try to make it easier for people to use open data and contribute open data to the community. The question often arises: How much open data do we have? Another angle on this topic is: How much is open data growing? We provide access to dozens of data respositories through our various packages. We...

This post is based on the free and open source Creating-maps-in-R teaching resource for introducing R as a command-line GIS. R is well known as an language ideally suited for data processing, statistics and modelling. R has a number of spatial packages, allowing analyses that would require hundreds of lines of code in other languages to be implemented with...

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