Archive for Università Ca’ Foscari Venezia

diario dell’anno della peste³

Posted in Books, Kids, pictures, Travel, University life, Wines with tags , , , , , , , , , , , on March 6, 2022 by xi'an

Had a fantastic fortnight in Venezia, when visiting Roberto Casarin at Ca’Foscari. Living in the immediate vicinity of the campus meant enjoying a very quiet part of the city, not that Venezia was particularly crowded (except for the weekend which happened to be the beginning of a low-key Carnevale). I also managed to join the local swimming pool and thus enjoy the earliest morn session, while Xing daily on the way back the same people walking their kids to school or going to work.Read A history of what comes next by Sylvain Neuvel and part of Comes tumbling down by Seanan McGuire. Both books free from Tor.com. The former was nothing close to great, with an alien twist to the space conquest history and incomprehensible goals for a line of superheroes… The latter was near incomprehensible, albeit a Hugo Award 2021, but it is only when writing this post that I realised this was the fifth volume in a series. It may be that I will make an attempt at the first later, despite this inauspicious start!

Watched two further Korean TV series, Inspector Koo and Mad Dogs, the former being more realistic and mature than other K dramas, albeit with a super intelligent duo and a desintegration of the scenario structure as the story unfolds. The later is much more standard and not particularly worth recommending.

il cielo il limite [jatp]

Posted in pictures, Travel with tags , , , , , on February 11, 2022 by xi'an

Bayesian restricted likelihood with insufficient statistic [slides]

Posted in Books, pictures, Statistics, University life with tags , , , , , , , , , , , , , , on February 9, 2022 by xi'an

A great Bayesian Analysis webinar this afternoon with well-balanced presentations by Steve MacEachern and John Lewis, and original discussions by Bertrand Clarke and Fabrizio Rugieri. Which attracted 122 participants. I particularly enjoyed Bertrand’s points that likelihoods were more general than models [made in 6 different wordings!] and that this paper was closer to the M-open perspective. I think I eventually got the reason why the approach could be seen as an ABC with ε=0, since the simulated y’s all get the right statistic, but this presentation does not bring a strong argument in favour of the restricted likelihood approach, when considering the methodological and computational effort. The discussion also made me wonder if tools like VAEs could be used towards approximating the distribution of T(y) conditional on the parameter θ. This is also an opportunity to thank my friend Michele Guindani for his hard work as Editor of Bayesian Analysis and in particular for keeping the discussion tradition thriving!

ritorno a Venezia!

Posted in pictures, Travel, University life, Wines with tags , , , , , on February 8, 2022 by xi'an

living on the edge [of the canal]

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , , , on December 15, 2021 by xi'an

Last month, Roberto Casarin, Radu Craiu, Lorenzo Frattarolo and myself posted an arXiv paper on a unified approach to antithetic sampling. To which I mostly and modestly contributed while visiting Roberto in Venezia two years ago (although it seems much farther than that!). I have always found antithetic sampling fascinating, albeit mostly unachievable in realistic situations, except (and approximately) by quasi-random tools. The original approach dates back to Hammersley and Morton, circa 1956, when they optimally couple X=F⁻(U) and Y=F⁻(1-U), with U Uniform, although there is no clear-cut extension beyond pairs or above dimension one. While the search for optimal and feasible antithetic plans dried out in the mid-1980’s, despite near successes by Rubinstein and others, the focus switched to Latin hypercube sampling.

The construction of a general antithetic sampling scheme is based on sampling uniformly an edge within an undirected graph in the d-dimensional hypercube, under some (three) assumptions on the edges to achieve uniformity for the marginals. This construction achieves the smallest Kullback-Leibler divergence between the resulting joint and the product of uniforms. And it can be furthermore constrained to be d-countermonotonic, ie such that a non-linear sum of the components is constant. We also show that the proposal leads to closed-form Kendall’s τ and Spearman’s ρ. Which can be used to assess different d-countermonotonic schemes, incl. earlier ones found in the literature. The antithetic sampling proposal can be applied in Monte Carlo, Markov chain Monte Carlo, and sequential Monte Carlo settings. In a stochastic volatility example of the later (SMC) we achieve performances similar to the quasi-Monte Carlo approach of Mathieu Gerber and Nicolas Chopin.

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