Archive for Statistical Modeling

urgent call for two scholarships for COVID-19 research at the University of Insubria, Como, Italy

Posted in Statistics, Travel, University life with tags , , , , , , on August 13, 2020 by xi'an

My friend Antonietta Mira sent me this urgent call for two short-term research positions at her Italian university, in Como, Lombardia, Italy. The deadline is 25 August, 2020! (Please send any enquiry to her, not to me!)

Professor Antonietta Mira has received financial support for two scholarships, one for 6 and the other one for 9 months, for research related to COVID-19.

The gross monthly salary is 2666 Euros per month. Most of the research can be conducted remotely. The starting date of the scholarships will be approximately the first of October 2020.

The application deadline is 25/08/2020 at noon. The two calls only differ by the duration of the position (6 months or 9 months). Interested candidates should submit one application for each of the two calls unless they have a specific preference for one of the two durations.

Applications should be sent by e-mail to segreteria.dipsat[AT] with scanned handwritten signature and a copy of the identity card.

We are looking for is a brilliant researcher ideally with a doctorate in statistics or related subjects, autonomous in data analysis and estimation of models for forecasting. The researcher will collaborate with a research team with interdisciplinary competences. The research aims to predict the impact of the COVID-19 Wave on the Emergency and Urgency System in Lombardy.

If their PhD is not completed the applicants should finish their thesis by the end of the year or consider the research conducted under the fellowship as part of the research for the doctoral thesis.

The call is only available in Italian. Please note original documents and official translations are not needed when submitting the application. They will be only needed in case the applicant becomes the selected candidate for the position

visual effects

Posted in Books, pictures, Statistics with tags , , , , , , , , , , , on November 2, 2018 by xi'an

As advertised and re-discussed by Dan Simpson on the Statistical Modeling, &tc. blog he shares with Andrew and a few others, the paper Visualization in Bayesian workflow he wrote with Jonah Gabry, Aki Vehtari, Michael Betancourt and Andrew Gelman was one of three discussed at the RSS conference in Cardiff, last week month, as a Read Paper for Series A. I had stored the paper when it came out towards reading and discussing it, but as often this good intention led to no concrete ending. [Except concrete as in concrete shoes…] Hence a few notes rather than a discussion in Series B A.

Exploratory data analysis goes beyond just plotting the data, which should sound reasonable to all modeling readers.

Fake data [not fake news!] can be almost [more!] as valuable as real data for building your model, oh yes!, this is the message I am always trying to convey to my first year students, when arguing about the connection between models and simulation, as well as a defense of ABC methods. And more globally of the very idea of statistical modelling. While indeed “Bayesian models with proper priors are generative models”, I am not particularly fan of using the prior predictive [or the evidence] to assess the prior as it may end up in a classification of more or less all but terrible priors, meaning that all give very little weight to neighbourhoods of high likelihood values. Still, in a discussion of a TAS paper by Seaman et al. on the role of prior, Kaniav Kamary and I produced prior assessments that were similar to the comparison illustrated in Figure 4. (And this makes me wondering which point we missed in this discussion, according to Dan.)  Unhappy am I with the weakly informative prior illustration (and concept) as the amount of fudging and calibrating to move from the immensely vague choice of N(0,100) to the fairly tight choice of N(0,1) or N(1,1) is not provided. The paper reads like these priors were the obvious and first choice of the authors. I completely agree with the warning that “the utility of the the prior predictive distribution to evaluate the model does not extend to utility in selecting between models”.

MCMC diagnostics, beyond trace plots, yes again, but this recommendation sounds a wee bit outdated. (As our 1998 reviewww!) Figure 5(b) links different parameters of the model with lines, which does not clearly relate to a better understanding of convergence. Figure 5(a) does not tell much either since the green (divergent) dots stand within the black dots, at least in the projected 2D plot (and how can one reach beyond 2D?) Feels like I need to rtfm..!

“Posterior predictive checks are vital for model evaluation”, to wit that I find Figure 6 much more to my liking and closer to my practice. There could have been a reference to Ratmann et al. for ABC where graphical measures of discrepancy were used in conjunction with ABC output as direct tools for model assessment and comparison. Essentially predicting a zero error with the ABC posterior predictive. And of course “posterior predictive checking makes use of the data twice, once for the fitting and once for the checking.” Which means one should either resort to loo solutions (as mentioned in the paper) or call for calibration of the double-use by re-simulating pseudo-datasets from the posterior predictive. I find the suggestion that “it is a good idea to choose statistics that are orthogonal to the model parameters” somewhat antiquated, in that this sounds like rephrasing the primeval call to ancillary statistics for model assessment (Kiefer, 1975), while pretty hard to implement in modern complex models.

Statistical modeling and computation [apologies]

Posted in Books, R, Statistics, University life with tags , , , , , , , , , , , on June 11, 2014 by xi'an

In my book review of the recent book by Dirk Kroese and Joshua Chan,  Statistical Modeling and Computation, I mistakenly and persistently typed the name of the second author as Joshua Chen. This typo alas made it to the printed and on-line versions of the subsequent CHANCE 27(2) column. I am thus very much sorry for this mistake of mine and most sincerely apologise to the authors. Indeed, it always annoys me to have my name mistyped (usually as Roberts!) in references.  [If nothing else, this typo signals it is high time for a change of my prescription glasses.]