Publications associées à Modèle probit

Reliable data-driven decision-making through optimal transport

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Public R&D funding and new regional specialisations: The contingent role of technological relatedness

Wolf-Hendrik Peter Uhlbach

It is widely acknowledged that new technological specialisations of regions are to a large extent driven by the recombination of existing knowledge and capabilities. Yet, little is known about the role of policy in this process. To address this, we analyse ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2022

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2023

Robust Binary Models by Pruning Randomly-initialized Networks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Ziqi Zhao

Robustness to adversarial attacks was shown to require a larger model capacity, and thus a larger memory footprint. In this paper, we introduce an approach to obtain robust yet compact models by pruning randomly-initialized binary networks. Unlike adversar ...

2022

Simultaneous autoregressive models for spatial extremes

Emeric Rolland Georges Thibaud

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

WILEY2020

Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity

Anne-Clémence Corminboeuf, Ksenia Briling, Alberto Fabrizio, Andrea Grisafi

Machine-learning in quantum chemistry is currently booming, with reported applications spanning all molecular properties from simple atomization energies to complex mathematical objects such as the many-body wavefunction. Due to its central role in density ...

2020

Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation

Robert West, Eda Bayram, Alberto Garcia Duran

The existing literature on knowledge graph completion mostly focuses on the link prediction task. However, knowledge graphs have an additional incompleteness problem: their nodes possess numerical attributes, whose values are often missing. Our approach, d ...

2021

The socio-economic determinants of urban sprawl between 1980 and 2010 in Switzerland

Barbara Franziska Weilenmann, Irmi Seidl

Sprawl, as a particular characterisation of spatial extension of urbanised areas, is a contested issue. In this paper we provide an analysis of the major socio-economic determinants of changes in those urban patterns considered as sprawl in Switzerland. Ou ...

2017

Analyzing time sensitivity in the Paris subway: an interval data model approach

Matthieu Marie Cochon de Lapparent

We analyze individual travel discomfort-time tradeoffs in the Paris subway using stated choice experiments. The survey design allows to set up in a willingness-to-pay space to estimate the distributions of elasticities of values of travel time to crowd den ...

Springer2016

Distributionally Robust Logistic Regression

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ...

2015

Forecasting Uncertainty in Electricity Demand

Tri Kurniawan Wijaya

Generalized Additive Models (GAM) are a widely popular class of regression models to forecast electricity demand, due to their high accuracy, flexibility and interpretability. However, the residuals of the fitted GAM are typically heteroscedastic and lepto ...

2015

Estimation in Functional Lagged Regression

Lukasz Kidzinski

The paper introduces a functional time series (lagged) regression model. The impulse-response coefficients in such a model are operators acting on a separable Hilbert space, which is the function space L-2 in applications. A spectral approach to the estima ...

Wiley-Blackwell2015

A Multi-Dimensional Analysis of Hard Shoulder Running Systems

André-Gilles Dumont, Dimitrios Efthymiou, Sofia Samoili

The use of Hard Shoulder Running (HSR) systems is a relatively recent control policy aiming to ameliorate traffic conditions in recurrent congested networks. This ITS strategy attracts researchers and practitioners interest, in an attempt to assess its imp ...

2014

Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators

Michel Bierlaire

In this paper we show that individual attitudes of road carriers and their latent preferences toward specific freight service attributes do play a role in determining their mode choices. Specifically, we contribute to the empirical literature on freight ag ...

Elsevier Sci Ltd2013

Can Equity Volatility Explain the Global Loan Pricing Puzzle?

Pinar Uysal

This paper examines whether unobservable differences in firm volatility are responsible for the global loan pricing puzzle, which is the observation that corporate loan interest rates appear to be lower in Europe than in the United States. We analyze wheth ...

Oxford Univ Press Inc2013

Recent Progress in Polymorphism-Based Population Genetic Inference

Jeffrey David Jensen

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. Th ...

Oxford University Press2012

Robust binary regression

Stephan Morgenthaler, Sahar Hosseinian Ehrensberger

Robust procedures increase the reliability of the results of a data analysis. We studied such a robust procedure for binary regression models based on the criterion of least absolute deviation. The resulting estimating equation consists in a simple modific ...

Elsevier2011

Integrated schedule planning with supply-demand interactions for a new generation of aircrafts

Michel Bierlaire, Matteo Salani, Bilge Atasoy

We present an integrated schedule planning model where the décisions of schedule design, fleeting and pricing are made simultaneously. Pricing is integrated through a logit demand model where itinerary choice is modeled by defining the utilities of the alt ...

2012

Model misspecification in peaks over threshold analysis

Anthony Christopher Davison, Mária Süveges

Classical peaks over threshold analysis is widely used for statistical modeling of sample extremes, and can be supplemented by a model for the sizes of clusters of exceedances. Under mild conditions a compound Poisson process model allows the estimation of ...

2010