The generalized estimating equation (GEE) approach of Zeger and Liang facilitates analysis of data collected in longitudinal, nested, or repeated measures designs. GEEs use the generalized linear model to estimate more efficient and unbiased regression parameters relative to ordinary least squares regression in part because they permit specification of a working correlation matrix that accounts...

Despite traditional four-step model is the most prominent model in majority of travel demand analysis, it does not represent the potential correlations within different travel dimensions. As a result, some researches have suggested the use of choice modelling instead. However, most of them have represented travel dimensions individually rather than jointly. This research aims to fill this gap t...

R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested varying effects for mixtures of generalized linear models and multinomial regression for a-priori probabilities given concomitant variables are introduced. The use of the software in addition to model selection is demonstrate...

the combined effect of non-newtonian rheology and irreversible boundary reaction on dispersion in a herschel-bulkley fluid through a conduit (pipe/channel) is studied by using generalized dispersion model. the study explains the development of dispersive transport following the injection of a tracer in terms of three effective transport coefficients namely exchange, convective and dispersion co...

The authors propose pseudo-likelihood ratio tests for selecting semiparametric multivariate copula models in which the marginal distributions are unspecified, but the copula function is parameterized and can be misspecified. For the comparison of two models, the tests differ depending on whether the two copulas are generalized non-nested or generalized nested. For more than two models, the proc...

Learning in imbalanced domains is one of the recent challenges in machine learning and data mining. In imbalanced classification, data sets present many examples from one class and few from the other class, and the latter class is the one which receives more interest from the point of view of learning. One of the most used techniques to deal with this problem consists in preprocessing the data ...

Abstract We develop a new class of distributions, namely, the odd power generalized Weibull-G series (OPGW-GPS) distributions. present some special classes proposed distribution. Structural properties, have also been derived. conducted simulation study to evaluate consistency maximum likelihood estimates. Moreover, two real data examples on selected sets, illustrate usefulness The model outperf...