Current Issue : July - September Volume : 2014 Issue Number : 3 Articles : 6 Articles
The present paper is concerned with some self-interacting diffusions (xt,t = 0) living on Rd. These diffusions are solutions to\nstochastic differential equations: dxt = dbt\n- g(t)?V(xt - �µ �¯??)????, where ???? is the empirical mean of the process ??, ?? is an\nasymptotically strictly convex potential, and g is a given positive function. We study the asymptotic behaviour of x for three\ndifferent families of functions g. If g (t) = k log t with k small enough, then the process x converges in distribution towards the\nglobal minima of V, whereas if tg(t) ? c ?]0, ] or if g(t) ? g(8) ? [0, [, then x converges in distribution if and only\nif?xe-2V(x)dx = 0....
Within the context of clinical and other scientific research, a substantial need exists for an accurate determination of the point\nestimate in a lognormal mean model, given that highly skewed data are often present. As such, logarithmic transformations are\noften advocated to achieve the assumptions of parametric statistical inference. Despite this, existing approaches that utilize only a\nsample�s mean and variance may not necessarily yield the most efficient estimator. The current investigation developed and tested\nan improved efficient point estimator for a lognormal mean by capturing more complete information via the sample�s coefficient of\nvariation. Results of an empirical simulation study across varying sample sizes and population standard deviations indicated relative\nimprovements in efficiency of up to 129.47 percent compared to the usual maximum likelihood estimator and up to 21.33 absolute\npercentage points above the efficient estimator presented by Shen and colleagues (2006). The relative efficiency of the proposed\nestimator increased particularly as a function of decreasing sample size and increasing population standard deviation....
We consider optimal replacement policies with periodic imperfectmaintenance actions and minimal repairs.Themultistate system\nis minimally repaired at failure and imperfect maintenance actions are regularly carried out for preventive maintenance. The\ndiscrete modified Weibull distribution is introduced and some cost functions applied to this distribution are defined in order to\nbe minimized. Moreover, we assume that the costs of preventive maintenance depend on the degree of repair via a Kijima type 2\nmodel. For illustrative purpose, the obtained results are applied on sets of simulated data....
The renewal and renewal-intensity functions with minimal repair are explored for the Normal, Gamma, Uniform, and Weibull\nunderlying lifetime distributions. The Normal, Gamma, and Uniform renewal, and renewal-intensity functions are derived by\nthe convolution method. Unlike these last three failure distributions, the Weibull except at shape �Ÿ = 1 does not have a closedform\nfunction for the n-fold convolution. Since the Weibull is the most important failure distribution in reliability analyses, the\napproximate renewal and renewal-intensity functions of Weibull were obtained by the time-discretizing method using the Mean-\nValueTheorem for Integrals. A Matlab program outputs all reliability and renewal measures....
Based on the existing literature, this paper proposes two assumptions and designs a set of ecological supply chain performance\nevaluation indicators system. Because these indicators are interdependence for each other, this paper selects the analytic network\nprocess and builds the ANP networkmodel to evaluate the degree of ecological supply chain management practice among Chinese\nmanufacturing enterprises. The evaluation results show that there is different level indeed about the ecological supply chain\nmanagement level; the better the ecological supply chain management practice degree is, the more quickly the ecological supply\nchain management performance levels increase....
We study some mathematical properties of a new generator of continuous distributions with two extra parameters called the\nexponentiated half-logistic family. We present some special models. We investigate the shapes of the density and hazard rate\nfunction.We derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, probability\nweighted moments, Bonferroni and Lorenz curves, Shannon and R�´enyi entropies, and order statistics, which hold for any baseline\nmodel. We introduce two bivariate extensions of this family. We discuss the estimation of the model parameters by maximum\nlikelihood and demonstrate the potentiality of the new family by means of two real data sets....
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