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Seminario di Probabilita' a RM1
by Faggionato, Alessandra 12 Jan '18

12 Jan '18

Giovedi' 18 Gennaio, ore 12.00, Aula C Speaker: M. Maurelli (WIAS, Berlin) Title: Enhanced Sanov theorem for Brownian rough paths and an application to interacting particles Abstract: We establish a Sanov type large deviation principle for an ensemble of interacting Brownian rough paths. As application a large deviations principle for the (k-layer, enhanced) empirical measure of weakly interacting diffusions is obtained. This in turn implies a propagation of chaos result in rough path spaces and allows for a robust subsequent analysis of the particle system and its McKean-Vlasov type limit. The talk is based on a work in collaboration with J.D. Deuschel, P. Friz and M. Slowik -- ************************************************* Prof. Alessandra Faggionato http://www1.mat.uniroma1.it/~faggionato/ Department of Mathematics University "La Sapienza" Piazzale Aldo Moro, 5 00185 - Rome Office 5, Phone (0039) 06 49913252 *************************************************

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Seminario LA VECCHIA
by Matteo Ruggiero 12 Jan '18

12 Jan '18

STATISTICS SEMINARS @ COLLEGIO CARLO ALBERTO Venerdì 19 Gennaio 2018, alle ore 12:00, presso il nuovo edificio del Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terra' il seguente seminario: ------------------------------------------------ Davide LA VECCHIA (University of Geneva) SADDLEPOINT TECHNIQUES FOR DEPENDENT DATA Saddlepoint techniques provide numerically accurate, higher-order, small sample approximations to the distribution of estimators and test statistics. While a rich theory is available for saddlepoint techniques in the case of independently and identically distributed observations, only a few results have been obtained for dependent data. In this talk, we explain how to fill this gap in the literature. Using the method of the tilted-Edgeworth expansion, we devise new saddlepoint density approximations and saddlepoint test statistics in the settings of time series (short or long memory) and spatial processes (panel data models, with fixed effects, time-varying covariates and spatially correlated errors). We compare our new approximations to the ones obtained by standard asymptotic theory, by Edgeworth expansion and by resampling methods. The numerical exercises illustrate that our approximations yield accuracy's improvements, while preserving analytical tractability. ------------------------------------------------ Tutti gli interessati sono invitati a partecipare. Il seminario e' organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats <http://www.carloalberto.org/stats>) in collaborazione con il Collegio Carlo Alberto. Cordiali saluti, Matteo Ruggiero --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it

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ARPM min-workshop on "Advanced statistical techniques across disparate asset classes" at Roma Tre University
by Francesco Cesarone 11 Jan '18

11 Jan '18

Dear Colleagues, on 24 January 2018 from 9:30 to 13:00 (Aula 8, Department of Business Studies-Roma Tre University, Via Silvio D'Amico, 77 -00145, Roma ), Dr. Angela Loregian, senior researcher at ARPM, will hold a min-workshop on "Advanced statistical techniques across disparate asset classes". The attendance of the course is free, but for organizational reasons it is necessary to register by sending an email to francesco.cesarone(a)uniroma3.it with the following subjects: Name Surname - ARPM min-workshop. *About the Program.* *We introduce the concept of "risk driver" and **"invariant“, illustrating:* *- the asset-specific art of building risk drivers across the financial markets* *- the asset-agnostic science of applying statistics (econometrics and **machine learning) to extract the invariants and estimate their joint * *distribution. **Then, we translate the above statistical analysis into the asset-specific **joint distribution of instrument returns.* For more details, see the attached pdf file. We look forward to meeting you in Roma Tre! Best regards, Francesco Cesarone -- http://disa.uniroma3.it/qfw2018/ -- Francesco Cesarone - Ph.D. Ricercatore - Assistant Professor Facoltà di Economia Dipartimento di Studi Aziendali Università Roma Tre Via Silvio D'Amico, 77 00145 - Roma tel: +39 06 57335744 Skype: francesco.cesarone email: francesco.cesarone(a)uniroma3.it Studio n. 20 piano V WWW: http://host.uniroma3.it/docenti/cesarone/

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min-workshop on "Machine Learning and Big Data Analytics with MATLAB" at Roma Tre University
by Francesco Cesarone 11 Jan '18

11 Jan '18

Dear Colleagues, on 23 January 2018 from 14:00 to 17:00 (Computer Lab, ground floor, Department of Business Studies-Roma Tre University, Via Silvio D'Amico, 77 -00145, Roma), Dr. Francesca Perino, Application Engineer at MathWorks, will hold a min-workshop on "Machine Learning and Big Data Analytics with MATLAB". The attendance of the course is free, but for organizational reasons it is necessary to register to register on the following web page: https://it.mathworks.com/company/events/seminars/ml-da-with-matlab-2373496.… . *Overview* *At the heart of many financial applications are machine learning techniques used for risk classification, economic analysis, credit scoring, time series forecasting, estimating default probabilities, and data mining. Big data represents an opportunity for quantitative analysts and data scientists alike to impact the way organizations make informed business decisions. By building machine learning models that harness big data, a greater level of insight and confidence can be achieved.* *However, implementing and comparing machine learning techniques to choose the best method can be challenging. Furthermore, there is no single approach to solving the many challenges arising from working with big data. MATLAB minimizes these challenges by providing you with a number of built-in functions and tools for quick prototyping, integration, and scaling, to take you from initial prototype all the way to business-critical production system.* *In this session, we will introduce ways of working with big data systems, the different types of machine learning techniques in MATLAB, how to determine the best techniques for your problem by evaluating model performance, and rapidly deploying your machine learning models into production. We will cover several new workflows and data types in MATLAB and the toolboxes that have been designed to address the most common challenges with big data analytics and machine learning.* *Highlights* *Data management and integration with databases, live market data, and big data environments* *Efficient workflows for heterogenous time-series data using new data management capabilities* *Parallel Computing techniques to speed up long-running computations and deal with out-of-memory data* *Predictive modeling and using supervised machine learning techniques to build a credit rating engine* We look forward to meeting you in Roma Tre! Best regards, Francesco Cesarone -- http://disa.uniroma3.it/qfw2018/ -- Francesco Cesarone - Ph.D. Ricercatore - Assistant Professor Facoltà di Economia Dipartimento di Studi Aziendali Università Roma Tre Via Silvio D'Amico, 77 00145 - Roma tel: +39 06 57335744 Skype: francesco.cesarone email: francesco.cesarone(a)uniroma3.it Studio n. 20 piano V WWW: http://host.uniroma3.it/docenti/cesarone/

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[Forum SIS] : Seminari prof. Berger, Duke University
by Brunero Liseo 11 Jan '18

11 Jan '18

Avviso Ciclo di Seminari Il prof. James O. Berger, Duke University, https://en.wikipedia.org/wiki/Jim_Berger_(statistician) sarà ospite del Dipartimento MEMOTEF, Sapienza Università di Roma dal 22 al 26 gennaio 2018. Nel corso della settimana il prof. Berger terrà una serie di seminari su Bayesian Model Selection I seminari si terranno in Aula 6B, al piano terrà della facoltà di Economia, Via del Castro Laurenziano, 9, secondo il seguente orario: Lunedì 22 gennaio ore 11-13 Martedì 23 gennaio ore 16.30-18 Mercoledì 24 gennaio 11.30-13 Mercoledì 24 gennaio 14.30-16 I seminari sono rivolti ad un pubblico di dottorandi ma tutti gli interessati sono invitati a partecipare. Brunero Liseo -- ============================================ Brunero Liseo *Dip. di metodi e modelli per il territorio, l'economia e la finanza * *Sapienza Università di Roma* *Viale Castro Laurenziano, 9 Roma I-00161 *Tel. +39 06 49766973 Fax +39 06 4957606 *https://sites.google.com/a/uniroma1.it/bruneroliseo/ <https://sites.google.com/a/uniroma1.it/bruneroliseo/>* ============================================

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Correction: RISM School in Developements in SPDEs, first announcement
by gianmario tessitore 10 Jan '18

10 Jan '18

My pevious mail contained a missprint in the title of the school following is the correct announcement Gianmario Tessitore ======================================== Dear Colleagues, This is the first announcement of the upcoming sixth RISM school DEVELOPMENTS IN STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS in honor of Giuseppe Da Prato. It will take place in Varese during the week July 23-27, 2018 at the Riemann International School of Mathematics, Universita’ degli Studi dell'Insubria, and it will be directed by Martin Hairer. Please find the poster and further details at the link www.rism.it. The school will consist of three courses delivered by: Arnaud Debussche (Ecole Normale Superieure Rennes) Martin Hairer (Imperial College, London) Felix Otto (Max Planck Institute, Leipzig) and of three specialized talks aimed at presenting recent advances and challenges of contemporary research in SPDEs in connection with the work of Giuseppe Da Prato. Moreover young participants will be offered the possibility to present short communications on their own research. Interested people can register at the link http://www.rism.it/registration_rism5_45.html (a modest registration fee will cover 5 lunches and local transportations). IMPORTANT: PhD students, young researchers and postdocs are invited to apply for financial support towards lodging expenses by sending a CV to presidente(a)rism.it For organizing purposes we kindly ask participants to get registered as soon as possibe and, in any case, by the end of March 2018. With very best regards and wishes for a prosperous 2018, Scientific Committee: M. Hairer (Imperial College - London), S. Cerrai (University of Maryland), A. Debussche (ENS - Rennes), L. Zambotti (Universite Pierre et Marie Curie - Paris). Organizing Committee: D. Cassani (Univ. Insubria), M. Fuhrman (Univ. Milano), G. Guatteri (Politecnico di Milano), F. Masiero and G. Tessitore (Univ. Milano-Bicocca) -- Gianmario Tessitore Dipartimento di Matematica e Applicazioni Università degli Studi di Milano-Bicocca

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RISM School in Developements in SDEs, first announcement
by gianmario tessitore 10 Jan '18

10 Jan '18

Dear Colleagues, This is the first announcement of the upcoming sixth RISM school DEVELOPMENTS IN STOCHASTIC DIFFERENTIAL EQUATIONS in honor of Giuseppe Da Prato. It will take place in Varese during the week July 23-27, 2018 at the Riemann International School of Mathematics, Universita’ degli Studi dell'Insubria, and it will be directed by Martin Hairer. Please find the poster and further details at the link: www.rism.it. The school will consist of three courses delivered by: Arnaud Debussche (Ecole Normale Superieure Rennes) Martin Hairer (Imperial College, London) Felix Otto (Max Planck Institute, Leipzig) and of three specialized talks aimed at presenting recent advances and challenges of contemporary research in SPDEs in connection with the work of Giuseppe Da Prato. Moreover young participants will be offered the possibility to present short communications on their own research. Interested people can register at the link http://www.rism.it/registration_rism5_45.html (a modest registration fee will cover 5 lunches and local transportations). IMPORTANT: PhD students, young researchers and postdocs are invited to apply for financial support towards lodging expenses by sending a CV to presidente(a)rism.it For organizing purposes we kindly ask participants to get registered as soon as possibe and, in any case, by the end of March 2018. With very best regards and wishes for a prosperous 2018, Scientific Committee: M. Hairer (Imperial College - London), S. Cerrai (University of Maryland), A. Debussche (ENS - Rennes), L. Zambotti (Universite Pierre et Marie Curie - Paris). Organizing Committee: D. Cassani (Univ. Insubria), M. Fuhrman (Univ. Milano), G. Guatteri (Politecnico di Milano), F. Masiero and G. Tessitore (Univ. Milano-Bicocca) -- Gianmario Tessitore Dipartimento di Matematica e Applicazioni Università degli Studi di Milano-Bicocca

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Fwd: 3 year postdoc at Oxford in economic complex systems modeling
by Fabrizio Lillo 10 Jan '18

10 Jan '18

Ricevo e inoltro ---------------------------------------- Fabrizio Lillo Dipartimento di Matematica Università di Bologna ITALY Personal website: fabriziolillo.wordpress.com University website: www.unibo.it/sitoweb/fabrizio.lillo <http://fabriziolillo.wordpress.com/> phone: +39 050509159 <+39%20050%20509159> ---------- Forwarded message ---------- From: Doyne Farmer <Doyne.Farmer(a)inet.ox.ac.uk> Date: 2017-12-22 13:34 GMT+01:00 Subject: 3 year postdoc at Oxford in economic complex systems modeling To: Fabrizio Lillo <fabrizio.lillo(a)sns.it> We are seeking to appoint a Senior Research Associate to participate in the ‘Sensitive Intervention Points in the Transition to the Post-Carbon Society” project funded by the Oxford Martin School under the leadership of the Principal Investigators, Professor Doyne Farmer and Professor Cameron Hepburn. The project will study the transition to carbon neutral energy generation from economic, sociological and technological points of view. Key duties include playing a leadership role in managing the project, working closely with the principal investigators and the other members of the team to achieve the goals of the project; managing and undertaking academic research and write articles for publication in scientific journals; managing and co-ordinating research activities, administrative activities and grant reporting; playing a mentoring role, and act as a source of information and advice to other members of the group; disseminating research and presenting research outputs at conferences, workshops and to stakeholders; and developing ideas for generating research income and take a leadership role in finding additional sources of funding and making applications for research grants. The successful candidate will have ability to undertake interdisciplinary research, with strong skills in mathematics, programming, and large-scale data analysis; a PhD/DPhil in a field of quantitative science such as economics, mathematics, physics, computer science, social science, biology, statistics or engineering; fluency in written and spoken English; and a demonstrated track record in writing papers for publication. An ability to work in a demanding environment subject to deadlines and exacting professional and academic standards is essential. The appointment will be available for up to 36 months.

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Postdoctoral Research Associate position: "Postdoctoral Research Associate position “Laboratoire des Sciences du Climat et de l’Environnement” (LSCE, Gif-sur-Yvette, France) funded by CEA on "Event Attribution of Climate Changes with dynamically driven-Stochastic Weather Generators" (fwd)
by Michele Gianfelice 10 Jan '18

10 Jan '18

Ricevo ed inoltro p.c. . Cordialmente, m.gianfelice p.s: Among the Skills & diploma requested, the successful candidate should possess: - A PhD in Statistics, Applied Mathematics or related fields; - Strong bases on stochastic models including their statistical inference; - An excellent knowledge of R (recommended) or Python (second choice) programming languages; - English proficiency and attitude to work in an international research environment. ---------- Forwarded message ---------- Date: Wed, 10 Jan 2018 14:05:07 +0100 (CET) From: Davide Faranda <davide.faranda(a)lsce.ipsl.fr> Cc: Mathieu Vrac <mathieu.vrac(a)lsce.ipsl.fr> Subject: Postdoctoral Research Associate position: "Postdoctoral Research Associate position ?Laboratoire des Sciences du Clima t et de l?Environnement? (LSCE, Gif-sur-Yvette, France) funded by CEA on "E vent Attribution of Climate Changes with dynamically driven-Stochastic Weather Generators" Dear Colleague, (sorry for cross-posting) please circulate this announcement for a post-doctoral position at LSCE starting Spring 2018 for (at least) 16 months. Applications will be open untill January 31, 2018 Best Regards, Mathieu Vrac, Davide Faranda Postdoctoral Research Associate position ?Laboratoire des Sciences du Climat et de l?Environnement? (LSCE, Gif-sur-Yvette, France) funded by CEA on Event Attribution of Climate Changes with dynamically driven-Stochastic Weather Generators Expected starting date: Spring 2018. Duration: 16 months Context of the position: There is an increasing interest worldwide in assessing the extent to which recent extreme weather and climate events can be solely linked to natural climate variability or be significantly altered in frequency or intensity by human-induced climate change (Stott, 2016). Examples are numerous: Paris flood in June 2016, drought in Central Europe in Summer 2015, or the extremely cold European winter of 2009/10. The usual question is to know to what extent such extremes are linked to climate change, and if they are becoming (or will become) more or less frequent. Therefore, the science of ?event attribution? is evolving rapidly. This postdoctoral position is part of the European ERA4CS ?EUPHEME? project, whose one of the main objectives is to develop state-of-the-art event attribution methods for a range of timescales, and new techniques for evaluating their reliability. The vision of the EUPHEME project is to place extreme weather events in the context of climate variability and change, thereby helping European citizens adapt to a changing climate and mitigate its worst effects. Scientific context: Event attribution relies on comparisons of various statistics of extreme events between a ?factual world? (i.e., the world as we observe it or at least with the real physical forcings) and a ?counter-factual world? (i.e., the world as it would be without one or several given forcings, as human-induced greenhouse gas emissions). Those comparisons are usually performed based on a very high number (1000s of runs) of climate model simulations. One issue is that General circulation models are generally too expensive to be run as long as needed to compute such statistics and at the demanded resolution. Stochastic weather generators (SWGs) are therefore a valid alternative: they are statistical models calibrated on past observations to simulate as many datasets as desired with the same statistical properties [Wilks, 2010, 2012]. Moreover, the dynamics of atmospheric motions depends on the observed atmospheric states. Recently, a technique to measure such state-dependent dynamical properties have been found [Faranda et al., 2017] by the computation of the so-called local dimensions (a measure of the state disorder) and the local persistence. Preliminary studies have shown that such information can be lumped with the statistical model to obtain ?conditional SWGs? (e.g., Wong et al., 2014) providing simulations with a realistic dynamics. Main goals: The goal of the postdoctoral research is to provide both a theoretical framework and a numerical tool to build conditional SWGs driven by dynamical systems properties. - The first step will be to introduce such properties and indicators in simple autoregressive models to mimic the dynamical properties of univariate time series of climate variables and simple dynamical systems. - Those state-dependent indicators will then be used to condition progressively more sophisticated SWGs (e.g., Vrac et al., 2007), up to spatial models (i.e., simulating fields) for climate variables as wind, temperature or precipitation. - At each stage, the different conditional SWGs developed will be applied in an event attribution purpose to evaluate the improvements achieved or still needed, depending on the extreme events of interest. Skills & diploma requested: The successful candidate should possess: - A PhD in Statistics, Applied Mathematics, Statistical Physics, Climate sciences or related field; - Strong bases on stochastic models including their statistical inference; - A basic knowledge of climate dynamics; - An excellent knowledge of R (recommended) or Python (second choice) programming languages; - A basic knowledge of dynamical systems framework will be a plus but is not mandatory; - English proficiency and attitude to work in an international research environment. Geographical location & scientific team: This postdoctoral position will be located at Gif-sur-Yvette (France), in the ?Extremes ? Statistics ? Impacts ? Regionalization? (ESTIMR) scientific research team of the ?Laboratoire des Sciences du Climat et de l?Environnement? (LSCE). The ESTIMR team develops a methodological research aiming to better understand the climate data: statistical analyses of observations and simulations in order to investigate the variability and identify the trends, modelling of extreme events, detection and attribution of their changes, downscaling, bias adjustment of simulations, uncertainty modelling of climate projections, etc. The ESTIMR team leads and participates to international projects, from pure to more applied science project. The main activity of the team relies on the use and development of advanced statistical models via a strong multidisciplinary interaction among climatology, modelling and statistics. How to apply: Applications will be open until January 31, 2018 (or until the position is filled) and have to be submitted by e-mail to M. Vrac (mathieu.vrac[at]lsce.ipsl.fr) and D. Faranda (davide.faranda[at]lsce.ipsl.fr) as soon as possible and must include: - a CV (max 2 pages + Publication list), - A statement of research interests describing why the candidate fits the position (max 2 pages), - The names of at least two references including e-mail addresses and telephone numbers. More information on the ?Extremes ? Statistics ? Impacts ? Regionalization? (ESTIMR) team: http://www.lsce.ipsl.fr/en/Phocea/Vie_des_labos/Ast/ast_groupe.php?id_group… More information on the ?Laboratoire des Sciences du Climat et de l?Environnement? (LSCE): http://www.lsce.ipsl.fr/ References: Davide Faranda, Gabriele Messori and Pascal Yiou. Dynamical proxies of North Atlantic predictability and extremes. Scientific Reports, 7-41278, 2017 Vrac, M., M. Stein, K. Hayhoe. Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing. Climate Research, 2007, 34: 169-184, doi: 10.3354/cr00696 Wilks DS. Use of stochastic weather generators for precipitation downscaling. WIRES Clim Change 2010, 1(6):898?907 Wilks, D. S. (2012), Stochastic weather generators for climate-change downscaling, part II: multivariable and spatially coherent multisite downscaling. WIREs Clim Change, 3: 267?278. doi:10.1002/wcc.167 Wong, G., D. Maraun, M. Vrac, M. Widmann, J.M. Eden, and T. Kent, 2014: Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes. J. Climate, 27, 6940?6959, https://doi.org/10.1175/JCLI-D-13-00604.1 -- Davide Faranda LSCE - CNRS http://www.lsce.ipsl.fr/Pisp/davide.faranda/

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Master programmes at the University of Kent
by Fabrizio Leisen 10 Jan '18

10 Jan '18

Con preghiera di diffusione. Contattami pure se avete bisogno di ulteriori informazioni. Cordiali saluti, Fabrizio Leisen A postgraduate degree in Statistics from the University of Kent can open many doors both in industry and research. The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status. The School of Mathematics, Statistics and Actuarial Science has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. The School encourages all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes. The Statistics Group is forward-thinking, with varied research, and received high rankings in the Research Excellence Framework (REF) 2014 for research power and quality. An overview of the Statistics group activities can be found at https://www.kent.ac.uk/smsas/statistics/research/index.html For more information about postgraduate statistics programmes at Kent visit www.kent.ac.uk/smsas or contact the Admissions Officer: E: smsaspgadmissions(a)kent.ac.uk T: +44 (0) 1227 816050 Director: Fabrizio Leisen, F.Leisen(a)kent.ac.uk -- Fabrizio Leisen Reader in Statistics School of Mathematics, Statistics and Actuarial Sciences Sibson Building, University of Kent, Canterbury, CT2 7FS http://www.kent.ac.uk/smsas/statistics/our-people/profiles/leisen_fabrizio.… http://sites.google.com/site/fabrizioleisen/

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