Archive for Finland

day four at ISBA 22

Posted in Mountains, pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , , , , , , , , , , , , , on July 3, 2022 by xi'an

Woke up an hour later today! Which left me time to work on [shortening] my slides for tomorrow, run to Mon(t) Royal, and bike to St-Viateur Bagels for freshly baked bagels. (Which seemed to be missing salt, despite my low tolerance for salt in general.)

Terrific plenary lecture by Pierre Jacob in his Susie Bayarri’s Lecture about cut models!  Offering a very complete picture of the reasons for seeking modularisation, the theoretical and practical difficulties with the approach, and some asymptotics as well. Followed a great discussion by Judith on cut posteriors separating interest parameters from nuisance parameters, especially in semi-parametric models. Even introducing two priors on the same parameters! And by Jim Berger, who coauthored with Susie the major cut paper inspiring this work, and illustrated the concept on computer experiments (not falling into the fallacy pointed out by Martin Plummer at MCMski(v) in Chamonix!).

Speaking of which, the Scientific Committee for the incoming BayesComp²³ in Levi, Finland, had a working meeting to which I participated towards building the programme as it is getting near. For those interested in building a session, they should make preparations and take advantage of being together in Mon(t)réal, as the call is coming out pretty soon!

Attended a session on divide-and-conquer methods for dependent data, with Sanvesh Srivastava considering the case of hidden Markov models and block processing the observed sequence. Which is sort of justified by the forgettability of long-past observations. I wonder if better performances could be achieved otherwise as the data on a given time interval gives essentially information on the hidden chain at other time periods.

I was informed this morn that Jackie Wong, one speaker in our session tomorrow could not make it to Mon(t)réal for visa reasons. Which is unfortunate for him, the audience and everyone involved in the organisation. This reinforces my call for all-time hybrid conferences that avoid penalising (or even discriminating) against participants who cannot physically attend for ethical, political (visa), travel, health, financial, parental, or any other, reasons… I am often opposed the drawbacks of lower attendance, risk of a deficit, dilution of the community, but there are answers to those, existing or to be invented, and the huge audience at ISBA demonstrates a need for “real” meetings that could be made more inclusive by mirror (low-key low-cost) meetings.

Finished the day at Isle de Garde with a Pu Ehr flavoured beer, in a particularly lively (if not jazzy) part of the city…

Bayes Comp 2023

Posted in Mountains, Statistics, Travel, University life with tags , , , , , , , , , , on November 23, 2021 by xi'an

The official website for Bayes Comp 2023, taking place in Levi, Northern Finland, 15-17 March 2023, is on! And it’s beautiful.

ABC with inflated tolerance

Posted in Mountains, pictures, Statistics, Travel, University life with tags , , , , , , , , on December 8, 2020 by xi'an


For the last One World ABC seminar of the year 2020, this coming Thursday, Matti Vihola is speaking from Finland on his recent Biometrika paper “On the use of ABC-MCMC with inflated tolerance and post-correction”. To attend the talk, all is required is a registration on the seminar webpage.

The Markov chain Monte Carlo (MCMC) implementation of ABC is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We propose an approach that involves using a relatively large tolerance for the MCMC sampler to ensure sufficient mixing, and post-processing of the output which leads to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators and propose an adaptive ABC-MCMC algorithm, which finds a balanced tolerance level automatically based on acceptance rate optimization. Our experiments suggest that post-processing-based estimators can perform better than direct MCMC targeting a fine tolerance, that our confidence intervals are reliable, and that our adaptive algorithm can lead to reliable inference with little user specification.

visitors allowed in Svalbard

Posted in Statistics with tags , , , , , , , , , , , , , , , on November 8, 2020 by xi'an

MCMC importance samplers for intractable likelihoods

Posted in Books, pictures, Statistics with tags , , , , , , , , , , , on May 3, 2019 by xi'an

Jordan Franks just posted on arXiv his PhD dissertation at the University of Jyväskylä, where he discuses several of his works:

  1. M. Vihola, J. Helske, and J. Franks. Importance sampling type estimators based on approximate marginal MCMC. Preprint arXiv:1609.02541v5, 2016.
  2. J. Franks and M. Vihola. Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance. Preprint arXiv:1706.09873v4, 2017.
  3. J. Franks, A. Jasra, K. J. H. Law and M. Vihola.Unbiased inference for discretely observed hidden Markov model diffusions. Preprint arXiv:1807.10259v4, 2018.
  4. M. Vihola and J. Franks. On the use of ABC-MCMC with inflated tolerance and post-correction. Preprint arXiv:1902.00412, 2019

focusing on accelerated approximate MCMC (in the sense of pseudo-marginal MCMC) and delayed acceptance (as in our recently accepted paper). Comparing delayed acceptance with MCMC importance sampling to the advantage of the later. And discussing the choice of the tolerance sequence for ABC-MCMC. (Although I did not get from the thesis itself the target of the improvement discussed.)

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