DSpace Collection: Volume 8 Number 3
http://hdl.handle.net/10525/2455
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On the Busy Period in One Finite Queue of M/G/1 Type with Inactive Orbit
http://hdl.handle.net/10525/2463
Title: On the Busy Period in One Finite Queue of M/G/1 Type with Inactive Orbit<br/><br/>Authors: Dragieva, Velika<br/><br/>Abstract: The paper deals with a single server finite queuing systemwhere the customers, who failed to get service, are temporarily blocked inthe orbit of inactive customers. This model and its variants have manyapplications, especially for optimization of the corresponding models withretrials. We analyze the system in non-stationary regime and, usingthe discrete transformations method study, the busy period length andthe number of successful calls made during it.ACM Computing Classification System (1998): G.3, J.7.Wed, 01 Jan 2014 00:00:00 GMTGeneralized Priority Systems. Analytical Results and Numerical Algorithms
http://hdl.handle.net/10525/2462
Title: Generalized Priority Systems. Analytical Results and Numerical Algorithms<br/><br/>Authors: Mishkoy, Gheorghe<br/><br/>Abstract: A class of priority systems with non-zero switching times, referred asgeneralized priority systems, is considered.Analytical results regarding the distribution of busy periods, queue lengthsand various auxiliary characteristics are presented. These results can beviewed as generalizations of the Kendall functional equation and thePollaczek-Khintchin transform equation, respectively. Numerical algorithmsfor systems’ busy periods and traffic coefficients are developed.ACM Computing Classification System (1998): 60K25.Wed, 01 Jan 2014 00:00:00 GMTThe Methodology of the Subsistence Minimum Calculation for Developing Countries and its Computation on the Georgian Example
http://hdl.handle.net/10525/2461
Title: The Methodology of the Subsistence Minimum Calculation for Developing Countries and its Computation on the Georgian Example<br/><br/>Authors: Makalatia, Irakli; Krialashvili, Ketevani; Gerliani, Ramazi<br/><br/>Abstract: This article shows the social importance of subsistence minimum in Georgia.The methodology of its calculation is also shown. We propose ways of improvingthe calculation of subsistence minimum in Georgia and how to extend it for otherdeveloping countries.The weights of food and non-food expenditures in the subsistence minimumbaskets are essential in these calculations. Daily consumption value of the minimumfood basket has been calculated too. The average consumer expenditures on foodsupply and the other expenditures to the share are considered in dynamics.Our methodology of the subsistence minimum calculation is applied for thecase of Georgia. However, it can be used for similar purposes based on datafrom other developing countries, where social stability is achieved, and socialinequalities are to be actualized.ACM Computing Classification System (1998): H.5.3, J.1, J.4, G.3.Wed, 01 Jan 2014 00:00:00 GMTOn the Lp-Norm Regression Models for Estimating Value-at-Risk
http://hdl.handle.net/10525/2460
Title: On the Lp-Norm Regression Models for Estimating Value-at-Risk<br/><br/>Authors: Kumar, Pranesh; Kashanchi, Faramarz<br/><br/>Abstract: Analysis of risk measures associated with price series datamovements and its predictions are of strategic importance in the financial marketsas well as to policy makers in particular for short- and longterm planning for setting upeconomic growth targets. For example, oilprice risk-management focuses primarily onwhen and how an organization can best prevent the costly exposure to price risk.Value-at-Risk (VaR) is the commonly practised instrument to measure riskand is evaluated by analysing the negative/positive tail of the probability distributions of thereturns (profit or loss). In modelling applications, least-squares estimation (LSE)-basedlinear regression models are often employed for modeling and analyzing correlated data.These linear models are optimal and perform relatively well under conditions such as errorsfollowing normal or approximately normal distributions, being free of large size outliers and satisfyingthe Gauss-Markov assumptions. However, often in practical situations, the LSE-based linear regressionmodels fail to provide optimal results, for instance, in non-Gaussian situations especially when the errorsfollow distributions with fat tails and error terms possess a finite variance.This is the situation in case of risk analysis which involves analyzing tail distributions.Thus, applications of the LSE-based regression models may be questioned for appropriatenessand may have limited applicability. We have carried out the risk analysis of Iranian crude oil price databased on the Lp-norm regression models and have noted that the LSE-based models do not alwaysperform the best. We discuss results from the L1, L2 and L∞-norm based linear regression models.ACM Computing Classification System (1998): B.1.2, F.1.3, F.2.3, G.3, J.2.Wed, 01 Jan 2014 00:00:00 GMTDependence Structure of some Bivariate Distributions
http://hdl.handle.net/10525/2459
Title: Dependence Structure of some Bivariate Distributions<br/><br/>Authors: Dimitrov, Boyan<br/><br/>Abstract: Dependence in the world of uncertainty is a complex concept.However, it exists, is asymmetric, has magnitude and direction, and can bemeasured. We use some measures of dependence between random events toillustrate how to apply it in the study of dependence between non-numericbivariate variables and numeric random variables. Graphics show what isthe inner dependence structure in the Clayton Archimedean copula and theBivariate Poisson distribution. We know this approach is valid for studyingthe local dependence structure for any pair of random variables determinedby its empirical or theoretical distribution. And it can be used also to simulatedependent events and dependent r/v/’s, but some restrictions apply.ACM Computing Classification System (1998): G.3, J.2.Wed, 01 Jan 2014 00:00:00 GMTTeaching Statistics to Engineers: Learning from Experiential Data
http://hdl.handle.net/10525/2458
Title: Teaching Statistics to Engineers: Learning from Experiential Data<br/><br/>Authors: Mandrekar, Vidyadhar<br/><br/>Abstract: The purpose of the work is to claim that engineers can bemotivated to study statistical concepts by using the applications in their experienceconnected with Statistical ideas.The main idea is to choose a data from the manufacturing factility (for example,output from CMM machine) and explain that even if the parts used do not meetexact specifications they are used in production. By graphing the data one can showthat the error is random but follows a distribution, that is, there is regularily in the data instatistical sense. As the error distribution is continuous, we advocate that the concept ofrandomness be introducted starting with continuous random variables with probabilitiesconnected with areas under the density.The discrete random variables are then introduced in terms of decision connectedwith size of the errors before generalizing to abstract concept of probability.Using software, they can then be motivated to study statistical analysis of the datathey encounter and the use of this analysis to make engineering and management decisions.Wed, 01 Jan 2014 00:00:00 GMTFive Turning Points in the Historical Progress of Statistics - My Personal Vision
http://hdl.handle.net/10525/2457
Title: Five Turning Points in the Historical Progress of Statistics - My Personal Vision<br/><br/>Authors: von Collani, Elart<br/><br/>Abstract: Statistics has penetrated almost all branches of science and allareas of human endeavor. At the same time, statistics is not onlymisunderstood, misused and abused to a frightening extent, but it is also oftenmuch disliked by students in colleges and universities.This lecture discusses/covers/addresses the historical development of statistics,aiming at identifying the most important turning points that led to the present stateof statistics and at answering the questions “What went wrong with statistics?”and “What to do next?”.ACM Computing Classification System (1998): A.0, A.m, G.3, K.3.2.Wed, 01 Jan 2014 00:00:00 GMT