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Related publications (19)

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima’s Replica Formula)

Florent Gérard Krzakala, Alia Abbara

There has been a recent surge of interest in the study of asymptotic reconstruction performance in various cases of generalized linear estimation problems in the teacher-student setting, especially for the case of i.i.d standard normal matrices. Here, we g ...

2022

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Mats Julius Stensrud, Aaron Leor Sarvet

Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...

2021

Uncertainty propagation for the design study of the PETALE experimental programme in the CROCUS reactor

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Dimitri Rochman

The PETALE experimental programme in the CROCUS reactor intends to provide integral measurements to constrain stainless steel nuclear data. This article presents the tools and the methodology developed to design and optimize the experiments, and its operat ...

2020

Frequency domain theory for functional time series: Variance decomposition and an invariance principle

Neda Mohammadi Jouzdani

This paper is concerned with frequency domain theory for functional time series, which are temporally dependent sequences of functions in a Hilbert space. We consider a variance decomposition, which is more suitable for such a data structure than the varia ...

INT STATISTICAL INST2020

Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

Medical image segmentation is an important task forcomputer aided diagnosis. Pixelwise manual annotationsof large datasets require high expertise and is time consum-ing. Conventional data augmentations have limited benefitby not fully representing the unde ...

2020

Continuation Multilevel Monte Carlo Evolutionary Algorithm for Robust Aerodynamic Shape Design

Fabio Nobile, Pénélope Leyland, Michele Pisaroni

The majority of problems in aircraft production and operation require decisions made in the presence of uncertainty. For this reason, aerodynamic designs obtained with traditional deterministic optimization techniques seeking only optimality in a specific ...

2019

Validation of the ICRF antenna coupling code RAPLICASOL against TOPICA and experiments

Olivier Sauter, Basil Duval, Stefano Coda, Timothy Goodman, Yves Martin, Jean-Marc Moret, Duccio Testa, Patrick Blanchard, Bruno Marchand, Holger Reimerdes, Benoît Labit, Christian Gabriel Theiler, Cristian Sommariva, Alessandro Pau, Laurie Porte, Federico Alberto Alfredo Felici, Alexander Karpushov, Marc Gruber, Antoine Pierre Emmanuel Alexis Merle, Joan Decker, Umar Sheikh, Cristian Galperti, Yanis Andrebe, Pedro Andres Molina Cabrera, Pierre Jacquot, Lorenzo Anton-Louis Talà, Haomin Sun, Pamela Solange Valdés Undurraga, Andrea Salmi, Pascal Morel, Jose Felix Vega Stavro, Javier García Hernández, Richard Pitts, Yann Camenen, Jan Horacek, Raffaele Tito D'Agnolo, Roland Behn, Marco Wischmeier, Nicola Vianello, Federico Nespoli, Antonio José Pereira de Figueiredo, Alberto Bottino, Doohyun Kim, Emiliano Fable, Ben McMillan, Wouter Vijvers, Patrycja Nowak-Sliwinska, Andrea Scarabosio, Zhouji Huang, Cedric Kar-Wai Tsui, Kevin Henricus Annemarie Verhaegh, Anna Teplukhina, Dávid Wágner, Hoang Bao Le, Diego Carnevale, Claudio Marini, Thomas Binderup Jensen, Heinz Mueller, Donghyun Kim, Jennifer Kaitlyn Olsen, Himank Anand, Xiao Wang, Janir Nuno Ramos Antunes Da Cruz, Attila Bencze, Jose Vicente Sanchez Mut, Bernhard Sieglin, Michael Oliver Reinke, Allan Svejstrup Nielsen, Otto Asunta, Hartmut Zohm, Erwan Fabrice Koch, Ana Susnjara, Emanuele Poli, Matteo Fontana, Stefano Mattei, Gergely Papp, Lenke Horváth, Thomas Riedl, Wen Bin Chng, Giovanni Tardini, Daniel Molina Romero, Telmo David Ribeiro Da Costa, Dahye Choi

In this paper we validate the finite element code RAPLICASOL, which models radiofrequency wave propagation in edge plasmas near ICRF antennas, against calculations with the TOPICA code. We compare the output of both codes for the ASDEX Upgrade 2-strap ante ...

IOP Publishing Ltd2019

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

Haleh Yasrebi

Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-a ...

Oxford Univ Press2016

Data-driven coarse graining in action: Modeling and prediction of complex systems

Sebastian Krumscheid, Grigorios A. Pavliotis

In many physical, technological, social, and economic applications, one is commonly faced with the task of estimating statistical properties, such as mean first passage times of a temporal continuous process, from empirical data (experimental observations) ...

Amer Physical Soc2015

Statistical Unfolding Of Elementary Particle Spectra: Empirical Bayes Estimation And Bias-Corrected Uncertainty Quantification

Victor Panaretos, Mikael Johan Kuusela

We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in da ...

Inst Mathematical Statistics2015

Impact of synchrophasor measurement types and uncertainties on the accuracy of distribution system linear state estimators

Mario Paolone, Lorenzo Zanni, Sidi-Rachid Cherkaoui, Daniele Colangelo

The paper aims at assessing the effects of combined voltage and/or current synchrophasor measurements, and their associated uncertainties, on the accuracy of state estimators adopted in distribution systems. Such an assessment is first carried out with res ...

IEEE2015

Frequentist estimation of an epidemic's spreading potential when observations are scarce

Victor Panaretos, Andrea Kraus

We consider the problem of inferring the potential of an epidemic for escalating into a pandemic on the basis of limited observations in its initial stages. Classical results of Becker & Hasofer (J. R. Statist. Soc. B, 59, 415-29) illustrate that frequenti ...

Oxford University Press2014

Statistical Inference for Partially Observed Stochastic Epidemics

Andrea Kraus

This work is concerned with the estimation of the spreading potential of the disease in the initial stages of an epidemic. A speedy and accurate estimation is important for determining whether or not interventions are necessary to prevent a major outbreak. ...

EPFL2013

A new representation for multivariate tail probabilities

Jennifer Lynne Wadsworth, Jonathan A. Tawn

Existing theory for multivariate extreme values focuses upon characterizations of the distributional tails when all components of a random vector, standardized to identical margins, grow at the same rate. In this paper, we consider the effect of allowing t ...

Bernoulli Society for Mathematical Statistics and Probability2013

Asymptotic Inference For Partially Observed Branching Processes

Victor Panaretos, Andrea Kraus

We consider the problem of estimation in a partially observed discrete-time Galton-Watson branching process, focusing on the first two moments of the offspring distribution. Our study is motivated by modelling the counts of new cases at the onset of a stoc ...

Applied Probability Trust2011

Variance Stabilizing the Difference of Two Binomial Proportions

Stephan Morgenthaler, Robert Staudte

The article studies estimation of Delta = p(1) - p(2), the difference of two proportions p(1) and p(2), based on two independent Binomial experiments of size n(1) and n(2). The usual estimator, the difference between the two sample proportions, is variance ...

American Statistical Association2010

Numerical investigation of particle-laden thermally driven turbulent flows in enclosure

Riccardo Puragliesi

Nowadays, the global increase of energy demand and the necessity to satisfy high safety standards have led engineers and scientists to focus their efforts in order to understand and describe fundamental phenomena that are crucial for a correct design of th ...

EPFL2010