# Blog Archives

## another wrong entry

June 26, 2016
By

Quite a coincidence! I just came across another bug in Lynch’s (2007) book, Introduction to Applied Bayesian Statistics and Estimation for Social Scientists. Already discussed here and on X validated. While working with one participant to the post-ISBA softshop, we were looking for efficient approaches to simulating correlation matrices and came across the

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## Le Monde puzzle [#965]

June 13, 2016
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A game-related Le Monde mathematical puzzle: Starting with a pile of 10⁴ tokens, Bob plays the following game: at each round, he picks one of the existing piles with at least 3 tokens, takes away one of the tokens in this pile, and separates the remaining ones into two non-empty piles of arbitrary size. Bob

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## data challenge in Sardinia

June 9, 2016
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In what I hope is the first occurrence of a new part of ISBA conferences, Booking.com is launching a data challenge at ISBA 2016 next week. The prize being a trip to take part in their monthly hackathon. In Amsterdam. It would be terrific if our Bayesian conferences, including BayesComp, could gather enough data and

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## the new version of abcrf

June 6, 2016
By

A new version of the R package abcrf has been posted on Friday by Jean-Michel Marin, in conjunction with the recent arXival of our paper on point estimation via ABC and random forests. The new R functions come to supplement the existing ones towards implementing ABC point estimation: covRegAbcrf, which predicts the posterior covariance between

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## Le Monde puzzle [#964]

June 1, 2016
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A not so enticing Le Monde mathematical puzzle: Find the minimal value of a five digit number divided by the sum of its digits. This can formalised as finding the minimum of N/(a+b+c+d+e) when N writes abcde. And solved by brute force. Using a rough approach to finding the digits of a five-digit number, the

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## the random variable that was always less than its mean…

May 29, 2016
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Although this is far from a paradox when realising why the phenomenon occurred, it took me a few lines to understand why the empirical average of a log-normal sample is apparently a biased estimator of its mean. And why the biased plug-in estimator does not appear to present a bias. The picture below compares two

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## another riddle with a stopping rule

May 26, 2016
By
$another riddle with a stopping rule$

A puzzle on The Riddler last week that is rather similar to an earlier one. Given the probability (1/2,1/3,1/6) on {1,2,3}, what is the mean of the number N of draws to see all possible outcomes and what is the average number of 1’s in those draws? The second question is straightforward, as the proportions

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## occupancy rules

May 22, 2016
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$occupancy rules$

While the last riddle on The Riddler was rather anticlimactic, namely to find the mean of the number Y of empty bins in a uniform multinomial with n bins and m draws, with solution , this led

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## ABC random forests for Bayesian parameter inference

May 19, 2016
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Before leaving Helsinki, we arXived the paper Jean-Michel presented on Monday at ABCruise in Helsinki. This paper summarises the experiments Louis conducted over the past months to assess the great performances of a random forest regression approach to ABC parameter inference. Thus validating in this experimental sense the use of

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## Using MCMC output to efficiently estimate Bayes factors

May 18, 2016
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$Using MCMC output to efficiently estimate Bayes factors$

As I was checking for software to answer a query on X validated about generic Bayes factor derivation, I came across an R software called BayesFactor, which only applies in regression settings and relies on the Savage-Dickey representation of the Bayes factor when the null hypothesis writes as θ=θ⁰ (and possibly additional nuisance parameters with

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