The Fence Methods
The Fence Methods

Author: Jiming Jiang

Publisher: World Scientific

Published: 2015-09-22

Total Pages: 248

ISBN-13: 9814596086

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This book is about a recently developed class of strategies, known as the fence methods, which fits particularly well in non-conventional and complex model selection problems with practical considerations. The idea involves a procedure to isolate a subgroup of what are known as correct models, of which the optimal model is a member. This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from amongst those within the fence according to a criterion which can be made flexible. In particular, the criterion of optimality can incorporate consideration of practical interest, thus making model selection a real life practice.Furthermore, this book introduces a data-driven approach, called adaptive fence, which can be used in a wide range of problems involving determination of tuning parameters, or constants. Instead of relying on asymptotic theory, the fence focuses on finite-sample performance, and computation. Such features are particularly suitable to statistics in the new era.

Linear and Generalized Linear Mixed Models and Their Applications
Linear and Generalized Linear Mixed Models and Their Applications

Author: Jiming Jiang

Publisher: Springer Nature

Published: 2021-03-22

Total Pages: 343

ISBN-13: 1071612824

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This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis.

Large Sample Techniques for Statistics
Large Sample Techniques for Statistics

Author: Jiming Jiang

Publisher: Springer Nature

Published: 2022-04-04

Total Pages: 689

ISBN-13: 3030916952

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This book offers a comprehensive guide to large sample techniques in statistics. With a focus on developing analytical skills and understanding motivation, Large Sample Techniques for Statistics begins with fundamental techniques, and connects theory and applications in engaging ways. The first five chapters review some of the basic techniques, such as the fundamental epsilon-delta arguments, Taylor expansion, different types of convergence, and inequalities. The next five chapters discuss limit theorems in specific situations of observational data. Each of the first ten chapters contains at least one section of case study. The last six chapters are devoted to special areas of applications. This new edition introduces a final chapter dedicated to random matrix theory, as well as expanded treatment of inequalities and mixed effects models. The book's case studies and applications-oriented chapters demonstrate how to use methods developed from large sample theory in real world situations. The book is supplemented by a large number of exercises, giving readers opportunity to practice what they have learned. Appendices provide context for matrix algebra and mathematical statistics. The Second Edition seeks to address new challenges in data science. This text is intended for a wide audience, ranging from senior undergraduate students to researchers with doctorates. A first course in mathematical statistics and a course in calculus are prerequisites..

Oracle Database 10g Real Application Clusters Handbook
Oracle Database 10g Real Application Clusters Handbook

Author: K. Gopalakrishnan

Publisher: McGraw Hill Professional

Published: 2006-12-13

Total Pages: 448

ISBN-13: 0071632190

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Learn cutting-edge technology from Oracle experts Written by Oracle insiders, this comprehensive guide covers everything you need to know about Real Application Clusters -- low-cost hardware platforms that can rival and exceed the quality of service, availability, and scalability of the most expensive mainframe systems. Concepts covered are applicable to all previous versions of Oracle Tuning and troubleshooting tips, providing insight on the most advanced diagnostics available Detailed coverage of advanced RAC concepts Working code for all examples available online

Kafka: The Definitive Guide
Kafka: The Definitive Guide

Author: Gwen Shapira

Publisher: "O'Reilly Media, Inc."

Published: 2021-11-05

Total Pages: 499

ISBN-13: 1492043036

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Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes. Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. You'll examine: Best practices for deploying and configuring Kafka Kafka producers and consumers for writing and reading messages Patterns and use-case requirements to ensure reliable data delivery Best practices for building data pipelines and applications with Kafka How to perform monitoring, tuning, and maintenance tasks with Kafka in production The most critical metrics among Kafka's operational measurements Kafka's delivery capabilities for stream processing systems