R

Blogs on the R software.

coauthorship and citation networks

February 20, 2017
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coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

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coauthorship and citation networks

February 20, 2017
By
coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

Read more »

coauthorship and citation networks

February 20, 2017
By
coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

Read more »

A knapsack riddle [#2]?

February 16, 2017
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A knapsack riddle [#2]?

Still about this allocation riddle of the past week, and still with my confusion about the phrasing of the puzzle, when looking at a probabilistic interpretation of the game, rather than for a given adversary’s y, the problem turns out to search for the maximum of where the Y’s are Binomial B(100,p). Given those p’s, […]

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German Psychological Society fully embraces open data, gives detailed recommendations

February 15, 2017
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tl;dr: The German Psychological Society developed and adopted new recommendations for data sharing that fully embrace openness, transparency and scientific integrity. Key message is that raw data are an essential part of an empirical publication and mu...

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a knapsack riddle?

February 12, 2017
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a knapsack riddle?

The [then current now past] riddle of the week is a sort of multiarmed bandits optimisation. Of sorts. Or rather a generalised knapsack problem. The question is about optimising the allocation of 100 undistinguishable units to 10 distinct boxes against a similarly endowed adversary, when the loss function is and the distribution q of the […]

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A quick introduction to Apache Spark for statisticians

February 8, 2017
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A quick introduction to Apache Spark for statisticians

Introduction Apache Spark is a Scala library for analysing "big data". It can be used for analysing huge (internet-scale) datasets distributed across large clusters of machines. The analysis can be anything from the computation of simple descriptive statistics associated with the datasets, through to rather sophisticated machine learning pipelines involving data pre-processing, transformation, nonlinear model … Continue reading A quick introduction to Apache Spark for statisticians

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an accurate variance approximation

February 6, 2017
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an accurate variance approximation

In answering a simple question on X validated about producing Monte Carlo estimates of the variance of estimators of exp(-θ) in a Poisson model, I wanted to illustrate the accuracy of these estimates against the theoretical values. While one case was easy, since the estimator was a Binomial B(n,exp(-θ)) variate [in yellow on the graph], […]

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a well-hidden E step

February 2, 2017
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a well-hidden E step

A recent question on X validated ended up being quite interesting! The model under consideration is made of parallel Markov chains on a finite state space, all with the same Markov transition matrix, M, which turns into a hidden Markov model when the only summary available is the number of chains in a given state […]

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a well-hidden E step

February 2, 2017
By
a well-hidden E step

A recent question on X validated ended up being quite interesting! The model under consideration is made of parallel Markov chains on a finite state space, all with the same Markov transition matrix, M, which turns into a hidden Markov model when the only summary available is the number of chains in a given state […]

Read more »


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