Robustness And Complex Data Structures
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Robustness And Complex Data Structures
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Author : Claudia Becker
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-07-08
Robustness And Complex Data Structures written by Claudia Becker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-08 with Mathematics categories.
This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.
Robustness And Complex Data Structures
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Author : Claudia Becker
language : en
Publisher:
Release Date : 2013-04-30
Robustness And Complex Data Structures written by Claudia Becker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-30 with categories.
Modern Nonparametric Robust And Multivariate Methods
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Author : Klaus Nordhausen
language : en
Publisher: Springer
Release Date : 2015-10-05
Modern Nonparametric Robust And Multivariate Methods written by Klaus Nordhausen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-05 with Mathematics categories.
Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.
Robust Statistics For Signal Processing
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Author : Abdelhak M. Zoubir
language : en
Publisher: Cambridge University Press
Release Date : 2018-11-08
Robust Statistics For Signal Processing written by Abdelhak M. Zoubir and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-08 with Mathematics categories.
Understand the benefits of robust statistics for signal processing using this unique and authoritative text.
Crafting Data Driven Solutions Core Principles For Robust Scalable And Sustainable Systems
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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-12
Crafting Data Driven Solutions Core Principles For Robust Scalable And Sustainable Systems written by Peter Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-12 with Computers categories.
"Crafting Data-Driven Solutions: Core Principles for Robust, Scalable, and Sustainable Systems" stands as an essential resource for anyone tasked with developing, scaling, or managing applications where data is the pivotal component. This comprehensive guide delves into the architectural frameworks of data systems, elucidating the intricate interactions that influence performance, scalability, and reliability. From foundational principles to advanced theories in batch and stream processing, each chapter systematically unveils critical insights into data models, storage solutions, encoding techniques, replication strategies, and more, supported by real-world case studies and practical examples. Whether you are an experienced software architect, a developer keen to enhance your data system design skills, or a student preparing to navigate the complexities of big data, this book provides the deep knowledge and expert guidance needed to excel in the realm of data-driven systems. Empower yourself with the expertise to design resilient architectures that not only fulfill operational requirements but also scale gracefully with evolving data demands. Make "Crafting Data-Driven Solutions" your go-to reference for building next-generation systems that are robust, efficient, and sustainable.
Artificial Intelligence Big Data And Data Science In Statistics
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Author : Ansgar Steland
language : en
Publisher: Springer Nature
Release Date : 2022-11-15
Artificial Intelligence Big Data And Data Science In Statistics written by Ansgar Steland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Mathematics categories.
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book’s expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences
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Author : Maksym Luz
language : en
Publisher: John Wiley & Sons
Release Date : 2019-09-20
Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences written by Maksym Luz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Mathematics categories.
Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.
Supervised And Unsupervised Ensemble Methods And Their Applications
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Author : Oleg Okun
language : en
Publisher: Springer
Release Date : 2008-04-20
Supervised And Unsupervised Ensemble Methods And Their Applications written by Oleg Okun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-20 with Computers categories.
This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This workshop was held alongside the 3rd Iberian Conference on Pattern Recognition and Image Analysis.
Learning Typescript 5
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Author : Anna Richter
language : en
Publisher: GitforGits
Release Date : 2024-04-15
Learning Typescript 5 written by Anna Richter and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.
Programmers familiar with JavaScript who wish to learn more about TypeScript version 5.0 will find this book to be a resource of great value This book is ideal for developers who want to improve their front-end programming skills and integrate TypeScript with popular frameworks such as Angular and React. With clear explanations and hands-on examples, this book makes the transition from JavaScript to TypeScript easy and enjoyable. The book covers fundamental concepts such as static typing, type checking, and type inference, which will help you write more reliable and maintainable code. You'll learn how to use TypeScript's features to improve your development process, reduce bugs, and increase code quality. You'll learn about TypeScript's advanced features, such as interfaces, modules, and type narrowing techniques, through hands-on examples. To help you write more efficient and clean code, this book also covers how to use async/await and Promises to deal with asynchronous operations. "Learning TypeScript 5" offers solutions and troubleshooting techniques for the most common TypeScript challenges that developers face. You'll find out how to make your own error classes for different situations and how to use TypeScript's try/catch blocks to manage errors effectively. Integrating TypeScript with existing JavaScript applications, configuring the TypeScript compiler, and setting up TypeScript projects are all covered in the book. After finishing this book, you will have the knowledge and abilities to create scalable applications with TypeScript and work with frameworks such as Angular and React with ease. Whether you're starting a new project or upgrading an existing one, "Learning TypeScript 5" provides useful insights and practical knowledge to help you improve your development skills and take your programming to the next level. Key Learnings Use TypeScript with Angular and React to create scalable, reliable web apps. Create flawless code with TypeScript's type narrowing and control flow analysis. Maximize productivity in development and application speed by integrating TypeScript with Angular and React. Write cleaner, and more readable scripts with Promises and async/await. Use try/catch and other error handling methods to implement a robust system for managing errors. Master TypeScript's union types, interfaces, and modules for code organization. Maximize code quality with TypeScript's robust testing strategies and robust type-checking capabilities. Table of Content Introduction to TypeScript Working with Basic Types Functions in TypeScript Complex Types and Union Types Classes and Interfaces Modules and Namespaces TypeScript in Practice Runtime Behavior and Type Checking
Foundations Of Probability Theory
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Author : Himadri Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Foundations Of Probability Theory written by Himadri Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Foundations of Probability Theory" offers a thorough exploration of probability theory's principles, methods, and applications. Designed for students, researchers, and practitioners, this comprehensive guide covers both foundational concepts and advanced topics. We begin with basic probability concepts, including sample spaces, events, probability distributions, and random variables, progressing to advanced topics like conditional probability, Bayes' theorem, and stochastic processes. This approach lays a solid foundation for further exploration. Our book balances theory and application, emphasizing practical applications and real-world examples. We cover topics such as statistical inference, estimation, hypothesis testing, Bayesian inference, Markov chains, Monte Carlo methods, and more. Each topic includes clear explanations, illustrative examples, and exercises to reinforce learning. Whether you're a student building a solid understanding of probability theory, a researcher exploring advanced topics, or a practitioner applying probabilistic methods to solve real-world problems, this book is an invaluable resource. We equip readers with the knowledge and tools necessary to tackle complex problems, make informed decisions, and explore probability theory's rich landscape with confidence.