Commotonicity and maximum stop-loss premiums.

In this paper, we investigate the relationship between comonotonicity and stop-loss order. We prove our main results by using a characterization of stop-loss order within the framework of Yaari's (1987) dual theory of choice under risk. Wang and Dhaene (1997) explore related problems in the case of bivariate random variables. We extend their work to an arbitrary sum of random variables and present several examples illustrating our results.

Power loss in open cavity diodes and a modified Child Langmuir Law

Diodes used in most high power devices are inherently open. It is shown that under such circumstances, there is a loss of electromagnetic radiation leading to a lower critical current as compared to closed diodes. The power loss can be incorporated in the standard Child-Langmuir framework by introducing an effective potential. The modified Child-Langmuir law can be used to predict the maximum power loss for a given plate separation and potential difference as well as the maximum transmitted current for this power loss. The effectiveness of the theory is tested numerically.Comment: revtex4, 11 figure

Multivariate Estimation of Poisson Parameters

This paper is devoted to the multivariate estimation of a vector of Poisson means. A novel loss function that penalises bad estimates of each of the parameters and the sum (or equivalently the mean) of the parameters is introduced. Under this loss function, a class of minimax estimators that uniformly dominate the maximum likelihood estimator is derived. Crucially, these methods have the property that for estimating a given component parameter, the full data vector is utilised. Estimators in this class can be fine-tuned to limit shrinkage away from the maximum likelihood estimator, thereby avoiding implausible estimates of the sum of the parameters. Further light is shed on this new class of estimators by showing that it can be derived by Bayesian and empirical Bayesian methods. In particular, we exhibit a generalisation of the Clevenson-Zidek estimator, and prove its admissibility. Moreover, a class of prior distributions for which the Bayes estimators uniformly dominate the maximum likelihood estimator under the new loss function is derived. A section is included involving weighted loss functions, notably also leading to a procedure improving uniformly on the maximum likelihood method in an infinite-dimensional setup. Importantly, some of our methods lead to constructions of new multivariate models for both rate parameters and count observations. Finally, estimators that shrink the usual estimators towards a data based point in the parameter space are derived and compared

Iron loss in permanent-magnet brushless AC machines under maximum torque per ampere and flux weakening control

The airgap flux density distribution, flux density loci in the stator core, and the associated iron loss in two topologies of brushless AC motor, having a surface-mounted magnet rotor and an interior-mounted magnet rotor, respectively, are investigated when operated under maximum torque per ampere control in the constant torque mode and maximum power control in the flux-weakening mode. It is shown that whilst the interior magnet topology is known to be eminently suitable for flux-weakening operation, due to its high demagnetization withstand capability, its iron loss can be significantly higher than for a surface-mounted magnet machine

Dynamic modeling under linear-exponential loss

We develop a methodology of parametric modeling of time series dynamics when the underlying loss function is linear-exponential (Linex). We propose to directly model the dynamics of the conditional expectation that determines the optimal predictor. The procedure hinges on the exponential quasi maximum likelihood interpretation of the Linex loss and nicely fits the multiple error modeling framework. Many conclusions relating to estimation, inference and forecasting follow from results already available in the econometric literature. The methodology is illustrated using data on United States GNP growth and Treasury bill returns.Linear-exponential loss, optimal predictor, quasi maximum likelihood, multiple error model, autoregressive conditional durations