The present paper considers discrete probability models with exact computational properties. In relation to contingency tables this means closed form expressions of the maksimum likelihood estimate and its distribution. The model class includes what is known as decomposable graphical models, which can be characterized by a structured set of conditional independencies between some variables give...

Penna (2011) asks whether subjects with different follow-up times can be analysed through binomial regression. The answer to this question is “yes”. If the rate for a particular person is λ and they have been observed for a period of time (t), then the probability (p) of having an event during that time is equal to 1-e-λt. The equation can be re-arranged to give log[log(1-p)] = log(λ)+log(t). T...

This is cross sectional study based on 304 households (couples) with wives age less than 48 years, chosen from urban locality (city Lahore). Fourteen religious, demographic and socioeconomic factors of categorical nature like husband education, wife education, husband’s monthly income, occupation of husband, household size, husband-wife discussion, number of living children, desire for more chi...

A log-linear modelling will take quite a long time if the data involves many variables and if we try to deal with all the variables at once. Fienberg and Kim (1999) investigated the relationship between log-linear model and its conditional, and we will show how this relationship is employed to make the log-linear modelling easier. The result of this article applies to all the hierarchical log-l...

We investigate the problem of using continuous features in the maximum entropy (MaxEnt) model. We explain why the MaxEnt model with the moment constraint (MaxEnt-MC) works well with binary features but not with the continuous features. We describe how to enhance constraints on the continuous features and show that the weights associated with the continuous features should be continuous function...

We introduce, for the first time, a class of Birnbaum–Saunders nonlinear regression models. The new class of models generalizes the regression model described by Rieck and Nedelman [1991, A log-linear model for the Birnbaum–Saunders distribution, Technometrics, 33, 51–60]. We discuss maximum likelihood estimation for the parameters of the model, and derive closed-form expressions for the second...

This paper presents a simple regression test of parametric and semiparametric index models against more general semiparametric and nonparametric alternative models. The test is based on the regression coefficient of the restricted model residuals on the fitted values of the more general model. A goodness-of-fit interpretation is given to the regression coefficient, and the test is based on the ...