Concept

Test de normalité

Publications associées (16)

Data assimilation of post-irradiation examination data for fission yields from GEF

Andreas Pautz, Mathieu Hursin, Dimitri Rochman, Daniel Jerôme Siefman

Nuclear data, especially fission yields, create uncertainties in the predicted concentrations of fission products in spent fuel which can exceed engineering target accuracies. Herein, we present a new framework that extends data assimilation methods to bur ...

EDP SCIENCES S A2020

Bayesian regression explains how human participants handle parameter uncertainty

Michael Herzog, Jean-Pascal Théodor Pfister, Maya Anna Jastrzebowska, Mattew Pachai

Author summary How do humans make prediction when the critical factor that influences the quality of the prediction is hidden? Here, we address this question by conducting a simple psychophysical experiment in which participants had to extrapolate a parabo ...

2020

Data assimilation of post irradiation examination experiments to adjust fission yields

Andreas Pautz, Mathieu Hursin, Daniel Jerôme Siefman

Nuclear data, especially fission yields, create uncertainties in the predicted concentrations of fission products in spent fuel. Herein, we present a new framework that extends data assimilation methods to burnup simulations by using data from post-irradia ...

E D P SCIENCES2020

Reliable estimates of predictive uncertainty for an Alpine catchment using a non-parametric methodology

Anton Schleiss, Bettina Schaefli, José Pedro Gamito de Saldanha Calado Matos

Uncertainty affects hydrological modelling efforts from the very measurements (or forecasts) that serve as inputs to the more or less inaccurate predictions that are produced. Uncertainty is truly inescapable in hydrology and yet, due to the theoretical an ...

2017

Robust Portfolio Optimization

Zheng Wei Yap

Since the 2008 Global Financial Crisis, the financial market has become more unpredictable than ever before, and it seems set to remain so in the forseeable future. This means an investor faces unprecedented risks, hence the increasing need for robust port ...

EPFL2017

Inequality in genetic cancer risk suggests bad genes rather than bad luck

Mats Julius Stensrud

Heritability is often estimated by decomposing the variance of a trait into genetic and other factors. Interpreting such variance decompositions, however, is not straightforward. In particular, there is an ongoing debate on the importance of genetic factor ...

2017

Revisiting the Generality of the Rank-based Human Mobility Model

Daniel Gatica-Perez, Darshan Santani

Location-based social networks, in addition to revealing users' online social network, also informs users' actual movements in the offline physical world. Due to this, they have recently been used in large-scale mobility and urban studies. In this paper, u ...

2013

Bayesian Semiparametrics for Modelling the Clustering of Extreme Values

Thomas Lugrin

Extreme events can be statistically characterised as excesses of a high threshold. Inference in this case has to account for dependence between excesses. The peaks over threshold approach suggests pre-processing the series by defining clusters of successiv ...

2013

On Optimal Two Sample Homogeneity Tests for Finite Alphabets

Jayakrishnan Unnikrishnan

Suppose we are given two independent strings of data from a known finite alphabet. We are interested in testing the null hypothesis that both the strings were drawn from the same distribution, assuming that the samples within each string are mutually indep ...

Ieee2012

Applying the Multivariate Time-Rescaling Theorem to Neural Population Models

Joao Emanuel Felipe Gerhard

Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on ne ...

Massachusetts Institute of Technology Press2011

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