Concept

Quasi-likelihood

Related publications (30)

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Martin Vetterli, Luciano Sbaiz, Yue Lu, Feng Yang

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera or the gigapixel digital film camera. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor re ...

2010

A generic calibration framework for joint estimation of car following models using microscopic data

Microscopic simulation models have become widely applied tools in traffic engineering. Nevertheless, parameter identification of these models remains a difficult task. This is for one caused by the fact that parameters are generally not directly observable ...

2010

Estimation of discrete choice models: extending BIOGEME

Michel Bierlaire, Mamy Nirina Fetiarison

Discrete choice models are constantly in evolution in the literature. Since they enable to capture wide range of situations, they have been widely used by researchers and also practitioners in several fields of applications including econometrics and trans ...

2009

Estimation of discrete choice models: extending BIOGEME

Michel Bierlaire, Mamy Nirina Fetiarison

2009

Estimation of discrete choice models: extending BIOGEME

Michel Bierlaire, Mamy Nirina Fetiarison

BIOGEME is a free software package for estimating by maximum likelihood a broad range of random utility models. It can estimate particularly Multivariate Extreme Value (MEV) models including the logit model, the nested logit model, the cross-nested logit m ...

2009

Robust inference for generalized linear models

Sahar Hosseinian Ehrensberger

Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...

EPFL2009

Fast high-dimensional Bayesian classification and clustering

Vahid Partovi Nia

We introduce a fast approach to classification and clustering applicable to high-dimensional continuous data, based on Bayesian mixture models for which explicit computations are available. This permits us to treat classification and clustering in a single ...

EPFL2009

Statistical inference for olfactometer data

Anthony Christopher Davison, Ingrid Ricard

Olfactometer experiments are used to determine the effect of odours on the behaviour of organisms such as insects or nematodes, and typically result in data comprising many groups of small overdispersed counts. We develop a non-homogeneous Markov chain mod ...

2007

General state-space models

Thomas Gsponer

In time series analysis state-space models provide a wide and flexible class. The basic idea is to describe an unobservable phenomenon of interest on the basis of noisy data. The first constituent of such a model is the so-called state equation, which char ...

EPFL2004

Adapted Generative Models For Face Verification

Samy Bengio

It has been shown previously that systems based on local features and relatively complex generative models, namely 1D Hidden Markov Models (HMMs) and pseudo-2D HMMs, are suitable for face recognition (here we mean both identification and verification). Rec ...

IDIAP2003

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