In this paper, a new voting system model is introduced as a linear transformation model. The size of compartmental populations in each political group corresponding to every voted subject, the population weights, the weighted votes policy against each political group, the “Yes” and “No” rates, the “No” rejection policy and the “Yes” increase policy are the inputs / outputs of the introduced lin...

Based on the idea of a dynamical symmetry group, algebraic models of nuclear structure have proven to be quite successful in describing a variety of collective nuclear spectra [1]. A common element in these models is the su(3) ⊃ so(3) reduction that defines a relation between the quadrupole degree of freedom of the system and its angular momentum, which is used to classify levels of the system ...

The process of globalization has continued to generate controversy on its impact on groups that are vulnerable to poverty. In this respect, there is evidence that farmers in most developing countries are increasingly vulnerable to poverty due to a number of reasons. One possible reason could be the limited access to the technologies that assist farmers in improving their production and later in...

Goldstein (1986) describes the analysis of the multilevel mixed effects linear model with random coefficients, where the variance and covariance components have a nested structure across levels. The purpose of the present note is to show how a simple extension to the formulae in that paper can accommodate cross-classifications of the components within any level of the nesting, thus enabling qui...

Multiplicative interaction models, such as Goodman's (1981) RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are suitable only for data sets with two or three predictor variables. Here, we discuss an optimal scaling model for analyzing the content of interaction effects in generalized linear models with...

In this paper we study the identiiability of nonparametric models, that is, models in which both the functional forms of the equations and the probability distributions of the disturbances remain unspeciied. Identiiability in such models does not mean uniqueness of parameters but rather uniqueness of the set of predictions of interest to the investigator. For example, predicting the eeects of c...

A non-linear gravitational model with a multidimensional geometry and quadratic scalar curvature is considered. For certain parameter ranges, the extra dimensions are stabilized if the internal spaces have negative constant curvature. As a consequence, the 4–dimensional effective cosmological constant as well as the bulk cosmological constant become negative. The homogeneous and isotropic exter...

In this paper, we study the Gevrey regularity of weak solutions for a class of linear and semi-linear kinetic equations, which are the linear model of spatially inhomogeneous Boltzmann equations without an angular cutoff.

This work connects the neocybernetic theory of elastic systems to modeling of a complex industrial process. It turns out that using simple mathematics combined with multilinear tools leads to linear models that can be used for monitoring and control. As an application example, electroless nickel plating is studied.

This article describes a class of heteroscedastic generalized linear regression models in which a subset of the regression parameters are rescaled nonparametrically, and develops efficient semiparametric inferences for the parametric components of the models. Such models provide a means to adapt for heterogeneity in the data due to varying exposures, varying levels of aggregation, and so on. Th...