Search results for "probability"
showing 10 items of 3417 documents
Inventory Control Under Parametric Uncertainty of Underlying Models
2013
A large number of problems in inventory control, production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty of underlying models. In the present paper we consider the case, where it is known that the underlying distribution belongs to a parametric family of distributions. The problem of determining an optimal decision rule in the absence of complete information about the underlying distribution, i.e., when we specify only the functional form of the distribution and leave some or all of its parameters unspecified, is seen to be a standard problem of statistical estimation. Unfortunately, the clas…
A New Technique of Invariant Statistical Embedding and Averaging in Terms of Pivots for Improvement of Statistical Decisions Under Parametric Uncerta…
2021
In this chapter, a new technique of invariant embedding of sample statistics in a decision criterion (performance index) and averaging this criterion via pivotal quantities (pivots) is proposed for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging in terms of pivotal quantities (ISE&APQ) is independent of the choice of priors and represents …
Generalized Multitarget Linear Regression with Output Dependence Estimation
2019
Multitarget regression has recently received attention in the context of modern, large-scale problems in which finding good enough solutions in a timely manner is crucial. Different proposed alternatives use a combination of regularizers that lead to different ways of solving the problem. In this work, we introduce a general formulation with several regularizers. This leads to a biconvex minimization problem and we use an alternating procedure with accelerated proximal gradient steps to solve it. We show that our formulation is equivalent but more efficient than some previously proposed approaches. Moreover, we introduce two new variants. The experimental validation carried out, suggests th…
A new strategy for effective learning in population Monte Carlo sampling
2016
In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.
On the stability analysis for impulsive switching system with time-varying delay
2014
This paper focuses on the stability and stabilization problem for a neutral impulsive switching system with time-varying delay. Based on LMI method and optimization technologies, some stability criteria are derived for this kind of system. Some example and numerical simulation are given to demonstrate the effectiveness of our theoretical results. Refereed/Peer-reviewed
Stochastic reconstruction of sandstones
2000
A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with prescribed two-point probability function, lineal path function, and ``pore size'' distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be s…
SMAA - Stochastic multiobjective acceptability analysis
1998
Stochastic multiobjective acceptability analysis (SMAA) is a multicriteria decision support technique for multiple decision makers based on exploring the weight space. Inaccurate or uncertain input data can be represented as probability distributions. In SMAA the decision makers need not express their preferences explicitly or implicitly; instead the technique analyses what kind of valuations would make each alternative the preferred one. The method produces for each alternative an acceptability index measuring the variety of different valuations that support that alternative, a central weight vector representing the typical valuations resulting in that decision, and a confidence factor mea…
Prospect theory and stochastic multicriteria acceptability analysis (SMAA)
2009
Abstract We consider problems where multiple decision makers (DMs) want to choose their most preferred alternative from a finite set based on multiple criteria. Several approaches to support DMs in such problems have been suggested. Prospect theory has appealed to researchers through its descriptive power, but rare attempts have been made to apply it to support multicriteria decision making. The basic idea of prospect theory is that alternatives are evaluated by a difference function in terms of gains and losses with respect to a reference point. The function is suggested to be concave for gains and convex for losses and steeper for losses than for gains. Stochastic multicriteria acceptabil…
Bayesian adaptive estimation: The next dimension
2006
Abstract We propose a new psychometric model for two-dimensional stimuli, such as color differences, based on parameterizing the threshold of a one-dimensional psychometric function as an ellipse. The Ψ Bayesian adaptive estimation method applied to this model yields trials that vary in multiple stimulus dimensions simultaneously. Simulations indicate that this new procedure can be much more efficient than the more conventional procedure of estimating the psychometric function on one-dimensional lines independently, requiring only one-fourth or less the number of trials for equivalent performance in typical situations. In a real psychophysical experiment with a yes–no task, as few as 22 tri…
Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise
2008
In this study stochastic analysis of non-linear dynamical systems under α-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of α-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with α/2- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function …