Archive for CRiSM

retrospective Monte Carlo

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , on July 12, 2016 by xi'an

the pond in front of the Zeeman building, University of Warwick, July 01, 2014The past week I spent in Warwick ended up with a workshop on retrospective Monte Carlo, which covered exact sampling, debiasing, Bernoulli factory problems and multi-level Monte Carlo, a definitely exciting package! (Not to mention opportunities to go climbing with some participants.) In particular, several talks focussed on the debiasing technique of Rhee and Glynn (2012) [inspired from von Neumann and Ulam, and already discussed in several posts here]. Including results in functional spaces, as demonstrated by a multifaceted talk by Sergios Agapiou who merged debiasing, deburning, and perfect sampling.

From a general perspective on unbiasing, while there exist sufficient conditions to ensure finite variance and aim at an optimal version, I feel a broader perspective should be adopted towards comparing those estimators with biased versions that take less time to compute. In a diffusion context, Chang-han Rhee presented a detailed argument as to why his debiasing solution achieves a O(√n) convergence rate in opposition the regular discretised diffusion, but multi-level Monte Carlo also achieves this convergence speed. We had a nice discussion about this point at the break, with my slow understanding that continuous time processes had much much stronger reasons for sticking to unbiasedness. At the poster session, I had the nice surprise of reading a poster on the penalty method I discussed the same morning! Used for subsampling when scaling MCMC.

On the second day, Gareth Roberts talked about the Zig-Zag algorithm (which reminded me of the cigarette paper brand). This method has connections with slice sampling but it is a continuous time method which, in dimension one, means running a constant velocity particle that starts at a uniform value between 0 and the maximum density value and proceeds horizontally until it hits the boundary, at which time it moves to another uniform. Roughly. More specifically, this approach uses piecewise deterministic Markov processes, with a radically new approach to simulating complex targets based on continuous time simulation. With computing times that [counter-intuitively] do not increase with the sample size.

Mark Huber gave another exciting talk around the Bernoulli factory problem, connecting with perfect simulation and demonstrating this is not solely a formal Monte Carlo problem! Some earlier posts here have discussed papers on that problem, but I was unaware of the results bounding [from below] the expected number of steps to simulate B(f(p)) from a (p,1-p) coin. If not of the open questions surrounding B(2p). The talk was also great in that it centred on recursion and included a fundamental theorem of perfect sampling! Not that surprising given Mark’s recent book on the topic, but exhilarating nonetheless!!!

The final talk of the second day was given by Peter Glynn, with connections with Chang-han Rhee’s talk the previous day, but with a different twist. In particular, Peter showed out to achieve perfect or exact estimation rather than perfect or exact simulation by a fabulous trick: perfect sampling is better understood through the construction of random functions φ¹, φ², … such that X²=φ¹(X¹), X³=φ²(X²), … Hence,

X^t=\varphi^{t-1}\circ\varphi^{t-2}\circ\ldots\circ\varphi^{1}(X^1)

which helps in constructing coupling strategies. However, since the φ’s are usually iid, the above is generally distributed like

Y^t=\varphi^{1}\circ\varphi^{2}\circ\ldots\circ\varphi^{t-1}(X^1)

which seems pretty similar but offers a much better concentration as t grows. Cutting the function composition is then feasible towards producing unbiased estimators and more efficient. (I realise this is not a particularly clear explanation of the idea, detailed in an arXival I somewhat missed. When seen this way, Y would seem much more expensive to compute [than X].)

CRiSM workshop on estimating constants [slides]

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , on May 4, 2016 by xi'an

A short announcement that the slides of almost all talks at the CRiSM workshop on estimating constants last April 20-22 are now available. Enjoy (and dicuss)!

contemporary issues in hypothesis testing

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , , , , on May 3, 2016 by xi'an

hipocontemptNext Fall, on 15-16 September, I will take part in a CRiSM workshop on hypothesis testing. In our department in Warwick. The registration is now open [until Sept 2] with a moderate registration free of £40 and a call for posters. Jim Berger and Joris Mulder will both deliver a plenary talk there, while Andrew Gelman will alas give a remote talk from New York. (A terrific poster by the way!)

estimating constants [impression soleil levant]

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , on April 25, 2016 by xi'an

The CRiSM workshop on estimating constants which took place here in Warwick from April 20 till April 22 was quite enjoyable [says most objectively one of the organisers!], with all speakers present to deliver their talks  (!) and around sixty participants, including 17 posters. It remains a exciting aspect of the field that so many and so different perspectives are available on the “doubly intractable” problem of estimating a normalising constant. Several talks and posters concentrated on Ising models, which always sound a bit artificial to me, but also are perfect testing grounds for approximations to classical algorithms.

On top of [clearly interesting!] talks associated with papers I had already read [and commented here], I had not previously heard about Pierre Jacob’s coupling SMC sequence, which paper is not yet out [no spoiler then!]. Or about Michael Betancourt’s adiabatic Monte Carlo and its connection with the normalising constant. Nicolas Chopin talked about the unnormalised Poisson process I discussed a while ago, with this feature that the normalising constant itself becomes an additional parameter. And that integration can be replaced with (likelihood) maximisation. The approach, which is based on a reference distribution (and an artificial logistic regression à la Geyer), reminded me of bridge sampling. And indirectly of path sampling, esp. when Merrilee Hurn gave us a very cool introduction to power posteriors in the following talk. Also mentioning the controlled thermodynamic integration of Chris Oates and co-authors I discussed a while ago. (Too bad that Chris Oates could not make it to this workshop!) And also pointing out that thermodynamic integration could be a feasible alternative to nested sampling.

Another novel aspect was found in Yves Atchadé’s talk about sparse high-dimension matrices with priors made of mutually exclusive measures and quasi-likelihood approximations. A simplified version of the talk being in having a non-identified non-constrained matrix later projected onto one of those measure supports. While I was aware of his noise-contrastive estimation of normalising constants, I had not previously heard Michael Gutmann give a talk on that approach (linking to Geyer’s 1994 mythical paper!). And I do remain nonplussed at the possibility of including the normalising constant as an additional parameter [in a computational and statistical sense]..! Both Chris Sherlock and Christophe Andrieu talked about novel aspects on pseudo-marginal techniques, Chris on the lack of variance reduction brought by averaging unbiased estimators of the likelihood and Christophe on the case of large datasets, recovering better performances in latent variable models by estimating the ratio rather than taking a ratio of estimators. (With Christophe pointing out that this was an exceptional case when harmonic mean estimators could be considered!)

afternoon on Bayesian computation

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , , on April 6, 2016 by xi'an

Richard Everitt organises an afternoon workshop on Bayesian computation in Reading, UK, on April 19, the day before the Estimating Constant workshop in Warwick, following a successful afternoon last year. Here is the programme:

1230-1315  Antonietta Mira, Università della Svizzera italiana
1315-1345  Ingmar Schuster, Université Paris-Dauphine
1345-1415  Francois-Xavier Briol, University of Warwick
1415-1445  Jack Baker, University of Lancaster
1445-1515  Alexander Mihailov, University of Reading
1515-1545  Coffee break
1545-1630  Arnaud Doucet, University of Oxford
1630-1700  Philip Maybank, University of Reading
1700-1730  Elske van der Vaart, University of Reading
1730-1800  Reham Badawy, Aston University
1815-late  Pub and food (SCR, UoR campus)

and the general abstract:

The Bayesian approach to statistical inference has seen major successes in the past twenty years, finding application in many areas of science, engineering, finance and elsewhere. The main drivers of these successes were developments in Monte Carlo methods and the wide availability of desktop computers. More recently, the use of standard Monte Carlo methods has become infeasible due the size and complexity of data now available. This has been countered by the development of next-generation Monte Carlo techniques, which are the topic of this meeting.

The meeting takes place in the Nike Lecture Theatre, Agriculture Building [building number 59].

CRiSM workshop on estimating constants [#2]

Posted in pictures, Statistics, Travel, University life, Wines with tags , , , , , , , , , on March 31, 2016 by xi'an

The schedule for the CRiSM workshop on estimating constants that Nial Friel, Helen Ogden and myself host next April 20-22 at the University of Warwick is now set as follows. (The plain registration fees are £40 and accommodation on the campus is available through the online form.)

April 20, 2016
11:45 — 12:30: Adam Johansen
12:30 — 14:00: Lunch
14:00 — 14:45: Anne-Marie Lyne
14:45 — 15:30: Pierre Jacob
15:30 — 16:00: Break
16:00 — 16:45: Roberto Trotta
17:00 — 18:00: ‘Elevator’ talks
18:00 — 20:00: Poster session, Cheese and wine

April 21, 2016
9:00 — 9:45: Michael Betancourt
9:45 — 10:30: Nicolas Chopin
10:30 — 11:00: Coffee break
11:00 — 11:45: Merrilee Hurn
11:45 — 12:30: Jean-Michel Marin
12:30 — 14:00: Lunch
14:00 — 14:45: Sumit Mukherjee
14:45 — 15:30: Yves Atchadé
15:30 — 16:00: Break
16:00 — 16:45: Michael Gutmann
16:45 — 17:30: Panayiota Touloupou
19:00 — 22:00: Dinner

April 22, 2016
9:00 — 9:45: Chris Sherlock
9:45 — 10:30: Christophe Andrieu
10:30 — 11:00: Coffee break
11:00 — 11:45: Antonietta Mira

contemporary issues on hypothesis testing

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , on March 2, 2016 by xi'an

the pond in front of the Zeeman building, University of Warwick, July 01, 2014At Warwick U., CRiSM is sponsoring another workshop, this time on hypothesis testing next Sept. 15 and 16 (just before the Glencoe race!). Registration and poster submission are already open. Most obviously, given my current interests, I am quite excited by the prospect of taking part in this workshop (and sorry that Andrew can only take part by teleconference!).