Concept

Linear probability model

Related publications (42)

Structural Identification of Piecewise-Linear Models of Genetic Regulatory Networks

We present a method for the structural identification of genetic regulatory networks (GRNs), based on the use of a class of Piecewise-Linear (PL) models. These models consist of a set of decoupled linear models describing the different modes of operation o ...

Mary Ann Liebert, Inc. 2 Madison Avenue Larchmont, NY 10538 USA2008

The Banff challenge: Statistical detection of a noisy signal

Anthony Christopher Davison

Particle physics experiments such as those run in the Large Hadron Collider result in huge quantities of data, which are boiled down to a few numbers from which it is hoped that a signal will be detected. We discuss a simple probability model for this and ...

2008

The Case for Structured Random Codes: Beyond Linear Models

Michael Christoph Gastpar

Recent work has shown that for some multi-user networks, carefully controlling the algebraic structure of the coding scheme may be just as useful as selecting the correct input distribution. In particular, for linear channel models, including finite field ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Numerical methods and models relevant to transportation applications

Michaël Clément Louis Ghislain Thémans

In this thesis, we focus on standard classes of problems in numerical optimization: unconstrained nonlinear optimization as well as systems of nonlinear equations. More precisely, we consider two types of unconstrained nonlinear optimization problems. On t ...

EPFL2007

Wavelet-Based Multi-Resolution Statistics for Optical Imaging Signals: Application to Automated Detection of Odour Activated Glomeruli in the Mouse Olfactory Bulb

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

Optical imaging techniques offer powerful solutions to capture brain networks processing in animals, especially when activity is distributed in functionally distinct spatial domains. Despite the progress in imaging techniques, the standard analysis procedu ...

Elsevier2007

WSPM: Wavelet-Based Statistical Parametric Mapping

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu

Recently, we have introduced an integrated framework that combines wavelet-based processing with statistical testing in the spatial domain. In this paper, we propose two important enhancements of the framework. First, we revisit the underlying paradigm; i. ...

Elsevier2007

Design and optimization of district energy systems

François Maréchal, Daniel Favrat, Céline Weber

District energy systems have the potential to decrease the CO2 emissions linked to energy services (heating, hot water, cooling and electricity), thanks to the implementation of large polygeneration energy conversion technologies, connected to a group of b ...

Elsevier2007

Recent methodological developments in discrete choice models

Michel Bierlaire

The role of discrete choice models in decision-making support has significantly grown during the past 20 years. This is particularly true in the context of marketing and transportation, where it is critical to understand and forecast choice behavior in a d ...

2006

Variance-Covariance perturbation analysis of a Linear Model

Pierre-Yves Gilliéron, Bertrand Merminod

In this paper the perturbation influence properties of the stochastic model (variance-covariance) in linear models is discussed in detail. Some very useful formulae are established about the variance-covariance perturbation influence on the model parameter ...

2003

Progress of the international H-mode power threshold database activity

Yves Martin

The International Global H-mode Threshold Database has been revised and cleaned from inadequate data for some tokamaks. This significantly reduces the scatter for the corresponding datasets. The resulting new analyses including all ten tokamaks yields resu ...

2002

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