Concept

Maximum spacing estimation

Related publications (234)

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High-Resolution Impulse Radio Ultra Wideband

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We propose a high resolution ranging algorithm for unsynchronized impulse radio Ultra-wideband (UWB) communication systems in gaussian noise. We pose the ranging problem as a Maximum Likelihood (ML) estimation problem for the channel delays and attenuation ...

2007

Resamping variance estimation in surveys with missing data

Anthony Christopher Davison

We discuss variance estimation by resampling in surveys in which data are missing. We derive a formula for jackknife linearization in the case of calibrated estimation with deterministic regression imputation, and compare the resulting variance estimates w ...

2007

Simulation of Clogging Phenomena in Natural Porous Media

David Andrew Barry, Alessandro Brovelli, Flavio Malaguerra

The objective of this study is to investigate the modelling of porosity and hydraulic conductivity changes in saturated porous media induced by the biological growth in pore space. Three different relationships between porosity changes and hydraulic conduc ...

2007

Dynamical Dirichlet Mixture Model

Jean-Marc Odobez, Le Chen

In this report, we propose a statistical model to deal with the discrete-distribution data varying over time. The proposed model -- HMM+DM -- extends the Dirichlet mixture model to the dynamic case: Hidden Markov Model with Dirichlet mixture output. Both t ...

IDIAP2007

Specification, estimation and validation of a pedestrian walking behavior model

Michel Bierlaire, Gianluca Antonini, Thomas Robin, Sabina Schneider

We propose and validate a model for pedestrian walking behavior, based on discrete choice modeling. Two main behaviors are identified: unconstrained and constrained. The constrained patterns are captured by a leader-follower model and by a collision avoida ...

2007

A heuristic for nonlinear global optimization relevant to discrete choice models estimation

Michel Bierlaire, Michaël Clément Louis Ghislain Thémans, Nicolas Zufferey

In most applications related to transportation, it is of major importance to be able to identify the global optimum of the associated optimization problem. The work we present in this paper is motivated by the optimization problems arising in the maximum l ...

2007

Steady-State Performance of Adaptive Diffusion Least-Mean Squares

Ali H. Sayed

We study the mean-square performance of a diffusion least mean-squares protocol proposed in recent work to address the problem of distributed estimation [1, 2]. By relying on energy conservation arguments [8] we derive closed form expressions for the mean- ...

IEEE2007

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

Sparse Probabilistic Classifiers

The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining this practice. Thus, when classification uncertainty has to be assessed, it i ...

2007

Sparse Probabilistic Classifiers

IDIAP2007