Use of Complex Variables for Solving Certain Elasticity Problems Involving Intersecting Boundaries
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Scheduling and Control of Queueing Networks
Applications of queueing network models have multiplied in the last generation, including scheduling of large manufacturing systems, control of patient flow in health systems, load balancing in cloud computing, and matching in ride sharing. These problems are too large and complex for exact solution, but their scale allows approximation. This book is the first comprehensive treatment of fluid scaling, diffusion scaling, and many-server scaling in a single text presented at a level suitable for graduate students. Fluid scaling is used to verify stability, in particular treating max weight policies, and to study optimal control of transient queueing networks. Diffusion scaling is used to control systems in balanced heavy traffic, by solving for optimal scheduling, admission control, and routing in Brownian networks. Many-server scaling is studied in the quality and efficiency driven Halfin-Whitt regime and applied to load balancing in the supermarket model and to bipartite matching in ride-sharing applications.
Michigan Health Statistics
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The Foundations of Statistical Inference;
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Orthogonal Polynomials in the Spectral Analysis of Markov Processes
In pioneering work in the 1950s, S. Karlin and J. McGregor showed that probabilistic aspects of certain Markov processes can be studied by analyzing orthogonal eigenfunctions of associated operators. In the decades since, many authors have extended and deepened this surprising connection between orthogonal polynomials and stochastic processes. This book gives a comprehensive analysis of the spectral representation of the most important one-dimensional Markov processes, namely discrete-time birth-death chains, birth-death processes and diffusion processes. It brings together the main results from the extensive literature on the topic with detailed examples and applications. Also featuring an introduction to the basic theory of orthogonal polynomials and a selection of exercises at the end of each chapter, it is suitable for graduate students with a solid background in stochastic processes as well as researchers in orthogonal polynomials and special functions who want to learn about applications of their work to probability.
Time Spent Awaiting Trial
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Sidney's Arcadia, a Comparison Between the Two Versions
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Guide to Consumer Markets; 1971
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Calculus for Students of Engineering and the Exact Sciences; 2
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Amerigo Vespucci, Pilot Major
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Foundations of the Theory of Probability
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Statistical Foundations, Reasoning and Inference
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master's students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.
Principles of Complex Analysis
This is a brief textbook on complex analysis intended for the students of upper undergraduate or beginning graduate level. The author stresses the aspects of complex analysis that are most important for the student planning to study algebraic geometry and related topics. The exposition is rigorous but elementary: abstract notions are introduced only if they are really indispensable. This approach provides a motivation for the reader to digest more abstract definitions (e.g., those of sheaves or line bundles, which are not mentioned in the book) when he/she is ready for that level of abstraction indeed. In the chapter on Riemann surfaces, several key results on compact Riemann surfaces are stated and proved in the first nontrivial case, i.e. that of elliptic curves.
Calculus for Students of Engineering and the Exact Sciences; 1
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Orthogonal Polynomials
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An Experimental Introduction to the Theory of Probability
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Morbidity Statistics From General Practice
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A Conspectus of the Province of Ontario
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Operational Methods in Applied Mathematics
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Reliability Theory and Practice
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Local Government Statistics
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Brush and Pencil; 8
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Theory and Application of Liapunov's Direct Method
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Harmonic Analysis on the Real Line
- Introduction. - Classes of Functions. - Fourier Series. - Fourier Transform. - Hilbert Transform. - Hardy Spaces and their Subspaces. - Hardy Inequalities. - Certain Applications.
Forest Resource Statistics, Cascade County, Montana; no.12
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The Theory of Branching Processes
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Rank Correlation Methods; 3rd Edition
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Non-classical Orthogonal Polynomials ..
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Final Vital Statistics Tables, Maryland.; 1962
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An Introduction To The Laplace Transformation
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Statistics [microform]
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Life; v.18 JY-D(1891)
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The Decennial Census, 1925
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Primer for Data Analytics and Graduate Study in Statistics
This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.
Finite Markov Chains
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Celtic Scotland
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The Genesis of Lam矇's Equation
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Inequalities
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Multiple Imputation of Missing Data in Practice
Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.
![Digest of the English Census of 1871 [electronic Resource]](https://cdn.kingstone.com.tw/english/images/product/7542/9781013587542.webp "Digest of the English Census of 1871 [electronic Resource]")
Digest of the English Census of 1871 [electronic Resource]
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Trigonometric Series; 2
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Final Vital Statistics Tables, Maryland.; 1956
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Principles of Mechanics of Solids and Fluids; 1
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Statistics, an Introduction
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Abstract of Statistical Returns in Judicial Matters for 1861 [microform]
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The Elements of Statics and Dynamics
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World Fresh Fruit Production Statistics; no.75
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface.We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Operational Calculus Based on the Two-sided Laplace Integral
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface.We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
