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 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...

Exponential dispersion models, which are linear exponential families with a dispersion parameter, are the prototype response distributions for generalized linear models. The Tweedie families are those exponential dispersion models with power mean-variance relationships. The normal, Poisson, gamma and inverse Gaussian distributions are Tweedie families. Apart from these special cases, Tweedie di...

This paper represents the comparison between Negative Binomial Regression model and Generalized Poisson Regression model for over-dispersion count data. For this comparison, we used BDHS 2007 data in where the response variable is the total children ever born which is a count data. When the response variable is count, then Poisson Regression Model as a Generalized Linear Model is widely and pop...

This paper considers double generalized linear models, which allow the mean and dispersion to be modelled simultaneously in a generalized linear model context. Estimation of the dispersion parameters is based on a χ1 approximation to the unit deviances, and the accuracy of the saddle-point approximation which underlies this is discussed. Approximate REML methods are developed for estimation of ...

Discrete data in the form of counts often exhibit extra variation that cannot be explained by a simple model, such as the binomial or the Poisson. Also, these data sometimes show more zero counts than what can be predicted by a simple model. Therefore, a discrete generalized linear model (Poisson or binomial) may fail to fit a set of discrete data either because of zero-inflation, because of ov...