This volume is an outgrowth of the "International Conference on Mathematical and Statistical Modeling" and covers recent advances in the field. Applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques are presented. The book is divided into nine major sections, which include distribution theory and applications, probability and statistics, order statistics and analysis, engineering modeling, extreme value theory, business and economics applications, statistical methods, applied mathematics, and discrete distributions.

This comprehensive reference work will appeal to a diverse audience from the statistical, applied mathematics, engineering, and economics communities. Practitioners, researchers, and graduate students in mathematical and statistical modeling, optimization, and computing will benefit from this work.

Contributors are prominent, distinguished, and well-respected researchers in the field of mathematical and statistical modeling Real-world applications to safety, reliability, life-testing, financial modeling, quality control, general inference, economics, engineering, as well as neural networks and computational techniques Good reference work for practitioners, researchers, and graduate students in statistics, applied mathematics, engineering, economics, and modeling Includes supplementary material: sn.pub/extras

Autorentext
N. BALAKRISHNAN, PhD, is Professor of Mathematics and Statistics at McMaster University in Hamilton, Ontario, Canada.V. B. NEVZOROV, PhD, DS, is Professor of Probability and Statistics at St. Petersburg State University in St. Petersburg, Russia.

Klappentext

This volume is an outgrowth of the "International Conference on Mathematical and Statistical Modeling" and covers recent advances in the field. Applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques are presented. The book is divided into nine major sections, which include distribution theory and applications, probability and statistics, order statistics and analysis, engineering modeling, extreme value theory, business and economics applications, statistical methods, applied mathematics, and discrete distributions. This comprehensive reference work will appeal to a diverse audience from the statistical, applied mathematics, engineering, and economics communities. Practitioners, researchers, and graduate students in mathematical and statistical modeling, optimization, and computing will benefit from this work.

Inhalt
Distribution Theory and Applications.- Enrique Castillo#x02019;s Contributions to Conditional Specification.- The Polygonal Distribution.- Conditionally Specified Models: New Developments and Applications.- Modelling of Insurance Claim Count with Hurdle Distribution for Panel Data.- Distance Based Association and Multi-Sample Tests for General Multivariate Data.- Probability and Statistics.- Empirical Bayes Assessment of the Hyperparameters in Bayesian.- Order Statistics and Analysis.- Negative Mixtures Order Statistics and Systems.- Models of Ordered Data and Products of Beta Random Variables.- Exact Inference and Optimal Censoring Scheme for a Simple Step-Stress Model Under Progressive Type-II Censorig.- Engineering Modeling.- Non Gaussian State Estimation in Power Systems.- Statistics Applied to Wave Climate on a Beach Profile.- Extreme Value Theory.- On Some Dependence Measures for Multivariate Extreme Value Distributions.- Ratio of Maximum to the Sum for Testing Super Heavy Tails.- Tail Behaviour An Empirical Study.- An Example of Real#x02013;Life Data Where the Hill Estimator is Correct.- Business and Economics Applications.- Deriving Credibility Premiums Under Different Bayesian Methodology.- The Influence of Transport Links on Disaggregation and Regionalization Methods in Interregional Input-Output Models Between Metropolitan and Remote Areas.- Statistical Methods.- Jackknife Bias Correction of a Clock Offset Estimator.- Pretesting in Polytomous Logistic Regression Models Based on Phi-divergence Measures.- A Unified Approach to Model Selection, Discrimination, Goodness of Fit and Outliers in Time Series.- Generalized Linear Models Diagnostics for Binary Data using Divergence Measures.- Applied Mathematics.- Some Problems in Geometric Processing of Surfaces.- Generalized Inverse Computation Based on an Orthogonal Decomposition Methodology.- Single and Ensemble Fault Classifiers Based on Features Selected by Multi-Objective Genetic Algorithms.- Feasibility Conditions in Engineering Problems Involving a Parametric System of Linear Inequalities.- Forecasting Nonlinear Systems with Neural Networks via Anticipated Synchronization.- Discrete Distributions.- The Discrete Half-Normal Distribution.- Parameter Estimation for Certain q-Hypergeometric Distributions.