Concept

Frequentist inference

Related publications (83)

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Functional Peaks-Over-Threshold Analysis for Complex Extreme Events

Most current risk assessment for complex extreme events relies on catalogues of similar events, either historical or generated artificially. In the latter, no existing methods produce completely new events with mathematically justified extrapolation above ...

EPFL2018

Distributed Inference over Multitask Graphs under Smoothness

Ali H. Sayed, Stefan Vlaski, Roula Nassif

This paper formulates a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. The smoothness requirement softens the tra ...

IEEE2018

Inference of genealogies with geolocalised genetic data

Natural populations present an abundant genetic variability. Like mutation or natural se- lection, dierent processes are at stake to generate this variability. Population genetics is a topic that emerged in the late 40's, thanks mainly to the biologists Fi ...

2017

A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation

Rudolf Haraksim

This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes' inference model. In the context of the inference of identity of source, the Likeliho ...

Elsevier Ireland Ltd2017

Likelihood estimators for multivariate extremes

Anthony Christopher Davison, Raphaël Huser

The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high t ...

Springer2016

Asteroid Deflection Campaign Design Integrating Epistemic Uncertainties

Patricia Egger, Sung Wook Paek

Asteroid deflection entails multiple sources of epistemic uncertainties and stochastic uncertainties. Epistemic uncertainties can be reduced by replenishing incomplete information with a better means of observation, whereas stochastic uncertainties are inh ...

Ieee2016

Objective Bayesian Model Selection

Thomas Lugrin

Frequentist and Bayesian approaches to statistics have long been seen as incompatible, but recent work has been done to try and unify them (Bayarri and Berger, 2004; Efron, 2005). Empirical Bayes, approximate Bayesian analysis, and the matching prior appro ...

2015

Statistics of Extremes

Anthony Christopher Davison, Raphaël Huser

Statistics of extremes concerns inference for rare events. Often the events have never yet been observed, and their probabilities must therefore be estimated by extrapolation of tail models fitted to available data. Because data concerning the event of int ...

Annual Reviews2015

Concepts of Information Content and Likelihood in Parameter Calibration for Hydrological Simulation Models

There remains a great deal of uncertainty about uncertainty estimation in hydrological modeling. Given that hydrology is still a subject limited by the available measurement techniques, it does not appear that the issue of epistemic error in hydrological d ...

Asce-Amer Soc Civil Engineers2015

Reliable Redundancy with Memristive-Biosensors to achieve Statistical Significance in Immunosensing

Giovanni De Micheli, Sandro Carrara, Danilo Demarchi, Francesca Puppo, Ardalan Lotfi

In this paper, we have investigated the redundancy in array of Memristive-Biosensors and find optimum number for devices to accomplish reliable biodetection. Our results lead less expensive sensor and reduce the low-reproducibility of this memristive metho ...

2015