the paper presents a possibility formulation of oneparameter estimation that unifies some usual probability formulations. Point and confidence interval estimation are unified in a single theoretical formulation and incorporated into estimators of an omnibus form: a possibility distribution. New relationships between continuous possibility distribution and probability concepts are established. T...

The nonlinear equations describing phase ordering dynamics can be closed by assuming the existence of an underlying Gaussian stochastic field which is nonlinearly related to the observable order parameter field. We discuss the relation between different implementations of the Gaussian assumption and consider the limitations of this assumption for phase ordering dynamics. The fact that the diffe...

In this paper, we derive a method to refine a Bayes network diagnostic model by exploiting constraints implied by expert decisions on test ordering. At each step, the expert executes an evidence gathering test, which suggests the test’s relative diagnostic value. We demonstrate that consistency with an expert’s test selection leads to non-convex constraints on the model parameters. We incorpora...

Traditional accounts of quantifier scope employ qualitative constraints or rules to account for scoping preferences. This paper outlines a feature-based parsing algorithm for a grammar with multiple simultaneous levels of representation, one of which corresponds to a partial ordering among quantifiers according to scope. The optimal such ordering (as well as the ranking of other orderings) is d...

We consider the minimization of submodular functions subject to ordering constraints. We show that this optimization problem can be cast as a convex optimization problem on a space of uni-dimensional measures, with ordering constraints corresponding to first-order stochastic dominance. We propose new discretization schemes that lead to simple and efficient algorithms based on zero-th, first, or...

Robust estimates for the performance of complicated queueing networks can be obtained by showing that the number of jobs in the network is stochastically comparable to a simpler, analytically tractable reference network. Classical coupling results on stochastic ordering of network populations require strong monotonicity assumptions which are often violated in practice. However, in most real-wor...

This paper aims to study a new stochastic order based upon discrete Laplace transforms. By this order, in setup where the sample size is random, having delta and nabla distributions, we obtain some ordering results involving ordinary fractional statistics. Some applications frailty models reliability are presented as well.

In this article, we introduce and study a new stochastic order of multivariate distributions, namely, the conditional likelihood ratio order. The proposed other orders are analyzed in case bivariate exponential distributions family. theoretical results obtained applied for studying reliability bridges affected by earthquakes. involves ordering; it resembles univariate but is much easier to veri...

Abstract The study describes the general concept of XLindley distribution. Forms density and hazard rate functions are investigated. Moreover, precise formulations for several numerical properties distributions derived. Extreme order statistics established using stochastic ordering, moment method, maximum likelihood estimation, entropies limiting We demonstrate new family’s adaptability by appl...