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An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the regression parameters does not exist if the data are completel ...
We discuss the identification of genetic networks based on a class of boolean gene activation rules known as hierarchically canalizing functions. We introduce a class of kinetic models for the concentration of the proteins in the network built on a family ...
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 ...
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 ...
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 ...
This paper investigates a non-linear mapping approach to extract robust features for ASR and separation of overlapping speech. Based on our previous studies, we continue to use two additional sound sources, namely, from the target and interfering speakers. ...
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 ...
We discuss the identification of genetic networks based on a class of boolean gene activation rules known as hierarchically canalizing functions. We introduce a class of kinetic models for the concentration of the proteins in the network built on a family ...
Predicting species distribution is of fundamental importance for ecology and conservation. However, distribution models are usually established for only one region and it is unknown whether they can be transferred to other geographical regions. We studied ...
In this note, the representations of extremal Dirichlet and logistic distributions are reviewed and extended. These new representations allow exact simulations of the spectral distribution functions and an extension of the extremal logistic case to dimensi ...
