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Robust discrete choice models with t-distributed kernel errors

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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

Alternative(s) to fractional-diffusion equations in bedload transport models.

Christophe Ancey, François Mettra, Valentin Métraux

The idea of stochastic sediment transport models emerged in the 1930s, notably with the doctoral work of Hans A. Einstein (1936). Einstein's seminal work gave impulse to several stochastic models, which usually led to thin-tailed or bounded distributions f ...

2010

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Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incur ...

2010

Statistical analysis of clusters of extreme events

Mária Süveges

The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...

EPFL2009

This thesis focuses on the decisional process of autonomous systems, and more particularly, on the way to take a decision when the time at disposal in order to assess the whole situation is shorter than necessary. Indeed, numerous systems propose solutions ...

EPFL2009

Computational neuroscience is a branch of the neurosciences that attempts to elucidate the principles underlying the operation of neurons with the help of mathematical modeling. In contrast with a number of fields pursuing a tightly related goal, such as m ...

EPFL2009

Estimation of discrete choice models under various sampling strategies

Michel Bierlaire

We first review the impact of various sampling strategies on the estimation of discrete choice models. In particular, consistent estimates of all parameters of a multinomial logit (MNL) model, except the constants, can be obtained from an exogenous sample ...

2009

In the presence of choice-based sampling strategies for data collection, the property of Multinomial Logit (MNL) models, that consistent estimâtes of all parameters but the constants can be obtained from an Exogenous Sample Maximum Likelihood (ESML) estima ...

2008

The estimation of multivariate extreme value models from choice-based samples

Michel Bierlaire

We consider an estimation procedure for discrete choice models in general and Multivariate Extreme Value (MEV) models in particular. It is based on a pseudo-likelihood function, generalizing the Conditional Maximum Likelihood (CML) estimator by Manski and ...

2007

Capturing correlation with subnetworks in route choice models

Michel Bierlaire, Emma Frejinger

When using random utility models for a route choice problem, a critical issue is the significant correlation among alternatives. There are basically two types of models proposed in the literature to address it: (i) a deterministic correction of the path ut ...

2007