R

Blogs on the R software.

Two meanings of priors, part II: Quantifying uncertainty about model parameters

January 17, 2017
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by Angelika Stefan & Felix Schönbrodt This is the second part of “Two meanings of priors”. The first part explained a first meaning – “priors as subjective probabilities of models”. While the first meaning of priors r...

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Two meanings of priors, part I: The plausibility of models

January 10, 2017
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by Angelika Stefan & Felix Schönbrodt When reading about Bayesian statistics, you regularly come across terms like “objective priors“, “prior odds”, “prior distribution”, and “normal prior”. However, it may not be intuitively clear...

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truncated normal algorithms

January 3, 2017
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truncated normal algorithms

Nicolas Chopin (CREST) just posted an entry on Statisfaction about the comparison of truncated Normal algorithms run by Alan Rogers, from the University of Utah. Nicolas wrote a paper in Statistics and Computing about a simulation method, which proposes a Ziggurat type of algorithm for this purpose, and which I do not remember reading, thanks […]

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May the Force of R be With You, Always!

January 2, 2017
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May the Force of R be With You, Always!

With a Telegram account connected to @TeleR, the force of R can always be with me, where I have data. The following is a screenshot of my mobile: If you want to have R where you are too, you only need a Telegram account; then, you have to search for...

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a Galton-Watson riddle

December 29, 2016
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a Galton-Watson riddle

The Riddler of this week has an extinction riddle which summarises as follows: One observes a population of N individuals, each with a probability of 10⁻⁴ to kill the observer each day. From one day to the next, the population decreases by one individual with probability K√N 10⁻⁴ What is the value of K that […]

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Ordering Categories within ggplot2 Facets

December 23, 2016
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Ordering Categories within ggplot2 Facets

I saw Simon Jackson’s recent blog post regarding ordering categories within facets. He proposed a way of dealing with the problem of ordering variables shared across facets within facets. This problem becomes apparent in text analysis where words are shared … Continue reading →

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Books on Scala for statistical computing and data science

December 22, 2016
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Books on Scala for statistical computing and data science

Introduction People regularly ask me about books and other resources for getting started with Scala for statistical computing and data science. This post will focus on books, but it’s worth briefly noting that there are a number of other resources available, on-line and otherwise, that are also worth considering. I particularly like the Coursera course … Continue reading Books on Scala for statistical computing and data science

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Scala for Data Science [book review]

December 22, 2016
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Scala for Data Science [book review]

This post will review the book: Scala for Data Science, Bugnion, Packt, 2016. Disclaimer: This book review has not been solicited by the publisher (or anyone else) in any way. I purchased the review copy of this book myself. I have not received any benefit from the writing of this review. Introduction On this blog … Continue reading Scala for Data Science [book review]

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Honoured to receive the Leamer-Rosenthal-Prize

December 19, 2016
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I’m honoured that the Berkeley Initiative for Transparency in the Social Sciences (BITSS) chose me for one of the 2016 Leamer-Rosenthal Prizes for Open Social Science! This award comes with a prize of $10,000 and “recognizes important contrib...

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Working with SBML using Scala

December 17, 2016
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Working with SBML using Scala

Introduction The Systems Biology Markup Language (SBML) is an XML-based format for representation and exchange of biochemical network models. SBML is supported by most systems biology modelling tools, allowing the export of a model in SBML from one tool and then reading in another tool. Because it offers a standard way of representing biochemical networks … Continue reading Working with SBML using Scala

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