Contribution Among Joint Tortfeasors and the Marital Immunity

Estimation of parameters in the classical Growth Curve model when the covariance matrix has some specific linear structure is considered. In our examples maximum likelihood estimators can not be obtained explicitly and must rely on optimization algorithms. Therefore explicit estimators are obtained as alternatives to the maximum likelihood estimators. From a discussion about residuals, a simple non-iterative estimation procedure is suggested which gives explicit and consistent estimators of both the mean and the linear structured covariance matrix.Original Publication:Martin Ohlson and Dietrich von Rosen, Explicit Estimators of Parameters in the Growth Curve Model with Linearly Structured Covariance Matrices, 2010, Journal of Multivariate Analysis, (101), 5, 1284-1295.http://dx.doi.org/10.1016/j.jmva.2009.12.023Copyright: Elsevier Science B.V., Amsterdamhttp://www.elsevier.com

Dynamics of colloidal particles with capillary interactions

We investigate the dynamics of colloids at a fluid interface driven by attractive capillary interactions. At submillimeter length scales, the capillary attraction is formally analogous to two-dimensional gravity. In particular it is a non-integrable interaction and it can be actually relevant for collective phenomena in spite of its weakness at the level of the pair potential. We introduce a mean-field model for the dynamical evolution of the particle number density at the interface. For generic values of the physical parameters the homogeneous distribution is found to be unstable against large-scale clustering driven by the capillary attraction. We also show that for the instability to be observable, the appropriate values for the relevant parameters (colloid radius, surface charge, external electric field, etc.) are experimentally well accessible. Our analysis contributes to current studies of the structure and dynamics of systems governed by long-ranged interactions and points towards their experimental realizations via colloidal suspensions.Comment: Matches version accepted for publication. New refs. added, misprints corrected in figs.6,8,9,1

Interrogation of Employees Concerning Union Matters as an Unfair Labor Practice

The problemof estimating parameters of amultivariate normal p-dimensional random vector is considered for a banded covariance structure reflecting mdependence. A simple non-iterative estimation procedure is suggested which gives an explicit, unbiased and consistent estimator of the mean and an explicit and consistent estimator of the covariance matrix for arbitrary p and m.Preliminary version published as Research Report 2008:3 at the Centre of Biostochastics Swedish University of Agricultural Sciences.The original publication is available at www.springerlink.com:Martin Ohlson, Zhanna Andrushchenko and Dietrich von Rosen, Explicit Estimators under m-Dependence for a Multivariate Normal Distribution, 2011, Annals of the Institute of Statistical Mathematics, (63), 1, 29-42.http://dx.doi.org/10.1007/s10463-008-0213-1Copyright: Springer Science Business Mediahttp://www.springerlink.com

A Percolation-Based Model Explaining Delayed Take-Off in New-Product Diffusion

A model of new-product diffusion is proposed in which a site-percolation dynamics represents socially-driven diffusion of knowledge about the product's characteristics in a population of potential buyers. A consumer buys the new product if her valuation of it is not below the price of the product announced by the firm in a given period. Our model attributes the empirical finding of a delayed ``take-off'' of a new product to a drift of the percolation dynamics from a non-percolating regime to a percolating regime. This drift is caused by learning-effects lowering the price of the product, or by network-effects increasing its valuation by consumers, with an increasing number of buyers.new-product diffusion, innovation adoption, spatial stochastic processes, percolation