Inactivation of the maternal or paternal X chromosome in a mammalian embryonic XX cell is believed to involve random choice between the two X's. We propose two alternative models. One suggests that choice is not random, while the other is consistent with random choice, but not one between two X's.

This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a different and independent random sample of N consumers in each period and each consumer makes only a single purchase decision. Under the second system, the same N consumers ...

This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed, utilizing Fourier-Laplace series on spheres. This approach offers a clear insight on the identification ...

Conventional random-coefficients models of conditional brand choice using panel data ignore the dependence of the random-coefficients distribution on the purchase frequencies. We show that this leads to biased estimates and propose a conditional likelihood approach to obtain unbiased estimates. Unlike alternative approaches that require observation of “no-purchase” occasions, our proposed metho...

We establish asymptotic vertex degree distribution and examine its relation to the clustering coefficient in two popular random intersection graph models of Godehardt and Jaworski (2001). For sparse graphs with positive clustering coefficient, we examine statistical dependence between the (local) clustering coefficient and the degree. Our results are mathematically rigorous. They are consistent...

Experimental results show that in large complex networks (such as internet, social or biological networks) there exists a tendency to connect elements which have a common neighbor. In theoretical random graph models, this tendency is described by the clustering coefficient being bounded away from zero. Complex networks also have power-law degree distributions and short average distances (small ...

This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed, utilizing Fourier-Laplace series on spheres. This approach offers a clear insight on the identification ...