a two-factor experiment with interaction between factors wherein observations follow an inverse gaussian model is considered. analysis of the experiment is approached via an empirical bayes procedure. the conjugate family of prior distributions is considered. bayes and empirical bayes estimators are derived. application of the procedure is illustrated on a data set, which has previously been an...

Abstract: Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm.   In addition pixel labeling corresponded to each pixel of true image was made by Bayes rule. In fact,...

Many discrete optimization problems of practical interest cannot be solved to optimality in the available time. A practical approach to these problems is to use heuristic algorithms, which do not guarantee the optimality of the solution but which, for many problems, can find nearly optimal solutions within a reasonable amount of computational time. The literature on heuristic algorithms often d...

Goldstein and Shaw (2002) developed Bayes linear kinematics describing how a Bayes linear analysis should be carried out when we only receive partial information which changes our beliefs about a vector of random quantities in some generalised way. In this paper we explore principles of local computation for Bayes linear kinematic updates. This theory is illustrated by the Bayes linear Bayes mo...

The pandemic has created a trend where most people have become addicted to the social media express thoughts, opinions, share reviews and also their daily life online. This contributed increasing volume of data over platforms. Based on these situations, been analyzed for benefits businesses organizations. Various sentiment analysis research conducted obtain public opinions such as products situ...

Abstract Naive Bayesian classification algorithm is widely used in big data analysis and other fields because of its simple fast structure. Aiming at the shortcomings naive Bayes algorithm, this paper uses feature weighting Laplace calibration to improve it, obtains improved algorithm. Through numerical simulation, it found that when sample size large, accuracy more than 99%, very stable; attri...

Air transportation is a very preferred type of for long-distance trips. This has made great progress, especially in the last 20 years with development technology. Thanks to its fast and safe, passenger capacity gradually increasing. Despite this situation, mortality rate quite high case an aircraft accident. For reason, hundreds people can die single In study, accidents that occurred world were...

In this paper, an effective approach based on the variable neighborhood search (VNS) algorithm is presented to solve the uncapacitated multilevel lot-sizing (MLLS) problems with component commonality and multiple end-items. A neighborhood structure for the MLLS problem is defined, and two kinds of solution move policies, i.e., move at first improvement (MAFI) and move at best improvement (MABI)...