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Exact Statistical Methods for Data Analysis
This book covers some recent developments in statistical inference. The author's main aim is to develop a theory of generalized p-values and generalized confidence intervals and to show how these … mehr »
geschrieben von Bell Weerahandi (Autor) und Sam Weerhandi (Autor) und Samaradasa Weerahandi (Autor)
Cross-over trials are experiments in which subjects, whether patients or healthy volunteers, are each given a number of treatments with the object being to study the differences between these …
Preface to the Second Edition.Preface to the First Edition.1. Introduction.2. Some Basic Considerations Concerning Estimation in Clinical Trials.3. The AB/BA Design with Normal Data.4. Other Outcomes …
The Handbook of Metaheuristics provides both the research and practitioner communities with a comprehensive coverage of the metaheuristic methodologies that have proven to be successful in a wide …
List of Contributing Authors.- Preface.- 1. Scatter Search and Path Relinking: Advances and Applications.- 2. An Introduction to Tabu Search.- 3. Genetic Algorithms.- 4. Genetic Programming; 5. A …
Nonlinearity and stochastic structural dynamics is of common interest to engineers and applied scientists belonging to many disciplines. Recent research in this area has been concentrated on the …
Higher order Averaging Method of Coefficients in Fokker-Planck Equation; N.D. Anh, N.D. Tinh. Recent Progress in Stochastic Bifurcation Theory; L. Arnold. Non-Resonant, Resonant Chaotic Dynamics in …
Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and …
Universal Lossless Data Compression.- Links Between Data Compression and Statistical Estimation.- Non Cumulated Mean Risk.- Gibbs Estimators.- Randomized Estimators and Empirical Complexity.- …
This book offers a superb overview of limit theorems and probability inequalities for sums of independent random variables. Unique in its combination of both classic and recent results, the book …
Notations and abbreviations; 1. Some basic concepts and theorems of probability theory; 2. Probability inequalities for sums of independent random variables; 3. Weak limit-theorems: convergence to …
This book provides state-of-the-art material in decision-making metaheuristics, from both an algorithm and application point of view. Audience: This book is suitable for professionals and students in …
Interior Point Methods for Linear Optimization is a comprehensive, thorough textbook on interior point methods (IPMs). The era of IPMs was initiated by N. Karmarkar's 1984 paper, which triggered …
List of figures.- List of tables.- Preface.- Acknowledgements.- Introduction.- I. Introdcution: Theory and Complexity.- Duality Theory for Linear Optimization.- A Polynomial Algorithm for the …
SAMPRIT CHATTERJEE, PHD, is Professor of Health Policy at Mount Sinai School of Medicine. He is also Professor Emeritus of Statistics at New York University. A well-known research scientist and …
The essentials of regression analysis through practical applications
Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful …
Preface. 1. Introduction. 2. Simple Linear regression. 3. Multiple Linear Regression. 4. Regression Diagnostics: Detection of Model Violations. 5. Qualitative Variables as Predictors. 6. …
University of Arkansas, Fayetteville, USA Virginia Tech, Blacksburg, USA …
Balancing applications with mathematical rigor, Probability Models in Operations Research provides an introduction to the use of probability to define models that have applications in industrial …
Probability Modeling Fundamentals. Analysis of Random Variables. Analysis of Multiple Random Variables. Bernoulli Processes. Discrete-Time Markov Chains. Poisson Processes. Renewal Processes. …
University of California at Los Angeles, USA …
Gives an introduction to advanced numerical methods. This textbook introduces several major numerical methods for solving various partial differential equations (PDEs) in science and engineering, …
Brief Overview of Partial Differential Equations. Finite Difference Methods for Parabolic Equations. Finite Difference Methods for Hyperbolic Equations. Finite Difference Methods for Elliptic …
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