Publications by xi'an
Computational Statistics
Do not resort to Monte Carlo methods unnecessarily. When I received this 2009 Springer-Verlag book, Computational Statistics, by James Gentle a while ago, I briefly took a look at the table of contents and decided to have a better look later… Now that I have gone through the whole book, I can write a short review on its scope and contents (to ...
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A ridiculous email
Wolfram Research presumably has a robot that sends automated email following postings on arXiv: Your article, “Evidence and Evolution: A review”, caught the attention of one of my colleagues, who thought that it could be developed into an interesting Demonstration to add to the Wolfram Demonstrations Project. The Demonstrations Project, launc...
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pimax(mcsm)
The function pimax from our package mcsm is used in to reproduce Figure 5.11 of our book Introducing Monte Carlo Methods with R. (The name comes from using the Pima Indian R benchmark as the reference dataset.) I got this email from Josué I ran the ‘pimax’ example from the mcsm manual, and it gave me the following message: > pimax(Nsim = 1...
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Typo in Bayesian Core [again]
Reza Seirafi from Virginia Tech sent me the following email about Bayesian Core, which alas is pointing out a real typo in the reversible jump acceptance probability for the mixture model: With respect to the expression provided on page 178 for the acceptance probability of the split move, I was wondering if the omission of the density of the au...
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Random sudokus [test]
Robin Ryder pointed out to me that 3 is indeed the absolute minimum one could observe because of the block constraint (bon sang, mais c’est bien sûr !). The distribution of the series of 3 digits being independent over blocks, the theoretical distribution under uniformity can easily be simulated: #uniform distribution on the block diagonal she...
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Confusing slice sampler
Most embarrassingly, Liaosa Xu from Virginia Tech sent the following email almost a month ago and I forgot to reply: I have a question regarding your example 7.11 in your book Introducing Monte Carlo Methods with R. To further decompose the uniform simulation by sampling a and b step by step, how you determine the upper bound for sampling of a?...
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Random [uniform?] sudokus
A longer run of the R code of yesterday with a million sudokus produced the following qqplot. It does look ok but no perfect. Actually, it looks very much like the graph of yesterday, although based on a 100-fold increase in the number of simulations. Now, if I test the adequation with a basic chi-square test (!), the result is highly negative: >...
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Random [uniform?] sudokus [corrected]
As the discrepancy [from 1] in the sum of the nine probabilities seemed too blatant to be attributed to numerical error given the problem scale, I went and checked my R code for the probabilities and found a choose(9,3) instead of a choose(6,3) in the last line… The fit between the true distribution and the observed frequencies is now much bett...
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ACM Transactions on Modeling and Computer Simulation
Pierre Lecuyer is the new editor of the ACM Transactions on Modeling and Computer Simulation (TOMACS) and he has asked me to become an Area Editor for the new area of simulation in Statistics. I am quite excited by this new Æditor’s hat, since this is a cross-disciplinary journal: The ACM Transactions on Modeling and Computer Simulation (TOMAC...
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Random sudokus [p-values]
I reran the program checking the distribution of the digits over 9 “diagonals” (obtained by acceptable permutations of rows and column) and this test again results in mostly small p-values. Over a million iterations, and the nine (dependent) diagonals, four p-values were below 0.01, three were below 0.1, and two were above (0.21 and 0.42). So...
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