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Principal Component Analysis and Randomness Test for Big Data Analysis, Tanaka-Yamawaki


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Автор: Tanaka-Yamawaki
Название:  Principal Component Analysis and Randomness Test for Big Data Analysis
ISBN: 9789811939662
Издательство: Springer
Классификация:

ISBN-10: 9811939667
Обложка/Формат: Hardback
Страницы: 152
Вес: 0.00 кг.
Серия: Evolutionary Economics and Social Complexity Science
Язык: English
Иллюстрации: X, 140 p. 43 illus.
Читательская аудитория: Science
Основная тема: Economics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the meaning of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science. First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series, C = XXT, where X represents a rectangular matrix of N rows and L columns and XT represents the transverse matrix of X. Because C is symmetric, namely, C = CT, it can be converted to a diagonal matrix of eigenvalues by a similarity transformation SCS-1 = SCST using an orthogonal matrix S. When N is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation). Then the RMT-PCA applied to high-frequency stock prices in Japanese and American markets is dealt with. This approach proves its effectiveness in extracting trendy business sectors of the financial market over the prescribed time scale. In this case, X consists of N stock- prices of length L, and the correlation matrix C is an N by N square matrix, whose element at the i-th row and j-th column is the inner product of the price time series of the length L of the i-th stock and the j-th stock of the equal length L. Next, the RMT-test is applied to measure randomness of various random number generators, including algorithmically generated random numbers and physically generated random numbers. The book concludes by demonstrating two applications of the RMT-test: (1) a comparison of hash functions, and (2) stock prediction by means of randomness, including a new index of off-randomness related to market decline.
Дополнительное описание: Big Data Analysis by Means of RMT-Oriented Methodologies.- Formulation of the RMT-PCA.- RMT-PCA and Stock Markets.- The RMT-test: New Tool to Measure the Randomness of a Given Sequence.- Application of the RMT-test.- Conclusion.- Appendix I: Introduction



Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems: Using the Methods of Stochastic Processes

Автор: Rahimi Tabar M. Reza
Название: Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems: Using the Methods of Stochastic Processes
ISBN: 3030184749 ISBN-13(EAN): 9783030184742
Издательство: Springer
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Цена: 16070.00 р.
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Описание:
​1 Introduction.- 2 Introduction to Stochastic Processes.- 3 Kramers-Moyal Expansion and Fokker-Planck Equation.- 4 Continuous Stochastic Process.- 5 The Langevin Equation and Wiener Process.- 6 Stochastic Integration, It o and Stratonovich Calculi.- 7 Equivalence of Langevin and Fokker-Planck Equations.- 8 Examples of Stochastic Calculus.-9 Langevin Dynamics in Higher Dimensions.- 10 Levy Noise Driven Langevin Equation and its Time Series-Based Reconstruction.- 11 Stochastic Processes with Jumps and Non-Vanishing Higher-Order Kramers-Moyal Coefficients.- 12 Jump-Diffusion Processes.- 13 Two-Dimensional (Bivariate) Jump-Diffusion Processes.- 14 Numerical Solution of Stochastic Differential Equations: Diffusion and Jump-Diffusion Processes.- 15 The Friedrich-Peinke Approach to Reconstruction of Dynamical Equation for Time Series: Complexity in View of Stochastic Processes.- 16 How To Set Up Stochastic Equations For Real-World Processes: Markov-Einstein Time Scale.- 17 Reconstruction of Stochastic Dynamical Equations: Exemplary Stationary Diffusion and Jump-Diffusion Processes.- 18 The Kramers-Moyal Coefficients of Non-Stationary Time series in The Presence of Microstructure (Measurement) Noise.- 19 Influence of Finite Time Step in Estimating of the Kramers-Moyal Coefficients.- 20 Distinguishing Diffusive and Jumpy Behaviors in Real-World Time Series.- 21 Reconstruction of Langevin and Jump-Diffusion Dynamics From Empirical Uni- and Bivariate Time Series.- 22 Applications and Outlook.- 23 Epileptic Brain Dynamics.


Analyzing Food Security Using Household Survey Data

Автор: Moltedo Ana
Название: Analyzing Food Security Using Household Survey Data
ISBN: 1464801339 ISBN-13(EAN): 9781464801334
Издательство: Mare Nostrum (Eurospan)
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Цена: 4019.00 р.
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Описание: "Since the end of the Second World War, the international community has been focusing on reducing the number and the proportion of people who suffer from hunger. Over time it became clear that no single indicator would provide a comprehensive picture of the food security situation. Rather, a suite of indicators is necessary to describe food insecurity in all its dimensions. The demand for evidence-based policies, which brings together providers such as statistical offices and users of food security indicators including policy makers and researchers, has also been increasing. The stand-alone software, ADePT-Food Security Module (available for free downloading), was developed to produce food security indicators from food consumption data collected in household surveys. These indicators, derived at the national and subnational levels, include the consumption of calories and macronutrients, the availability of micronutrients and amino acids, the distribution of calories and the proportion of people undernourished. The book focuses on the theory, methodology, and analysis of these indicators. It has five chapters beginning with a brief overview on concepts of food security. The theory and methodology are further described in the following chapter. To help users with the interpretation of the results some examples are given in chapter 3. Chapter 4 of the book provides guidelines for the preparation of the input datasets. Finally, chapter 5 explains how to use the software. Both the software and this book are products of decades of experience in analyzing food security. This project was made possible through collaboration between FAO and the World Bank, with financial support from the European Union."

Econometric Analysis of Panel Data

Автор: Baltagi Badi H.
Название: Econometric Analysis of Panel Data
ISBN: 3030539520 ISBN-13(EAN): 9783030539528
Издательство: Springer
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Цена: 9083.00 р.
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Описание: Introduction.- The One-Way Error Component Regression Model.- The Two-Way Error Component Regression Model.- Test of Hypotheses with Panel Data.- Heteroskedasticity and Serial Correlation in the Error Component Model.- Seemingly Unrelated Regressions with Error Components.- Simultaneous Equations with Error Components.- Dynamic Panel Data Models.- Unbalanced Panel Data Models.- Special Topics.- Limited Dependent Variables and Panel Data.- Nonstationary Panels.- Spatial Panel Data Models.

Environmental Valuation with Discrete Choice Experiments: Guidance on Design, Implementation and Data Analysis

Автор: Mariel Petr, Hoyos David, Meyerhoff Jьrgen
Название: Environmental Valuation with Discrete Choice Experiments: Guidance on Design, Implementation and Data Analysis
ISBN: 3030626687 ISBN-13(EAN): 9783030626686
Издательство: Springer
Цена: 4191.00 р.
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Описание: This open access book offers up-to-date advice and practical guidance on how to undertake a discrete choice experiment as a tool for environmental valuation. Compiled by leading experts in the field, the book promotes discrete choice analysis in environmental valuation through a more solid scientific basis for research practice.

Statistical Analysis of Operational Risk Data

Автор: de Luca Giovanni, Caritа Danilo, Martinelli Francesco
Название: Statistical Analysis of Operational Risk Data
ISBN: 3030425797 ISBN-13(EAN): 9783030425791
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk.

Panel Data Analysis

Автор: Baldev Raj; Badi H. Baltagi
Название: Panel Data Analysis
ISBN: 364250129X ISBN-13(EAN): 9783642501296
Издательство: Springer
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Цена: 13974.00 р.
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Описание: A number of advances have taken place in panel data analysisduring the pastthree decades and it continues to be one ofthe most active areas of research.

The Statistical Analysis of Categorical Data

Автор: Erling B. Andersen
Название: The Statistical Analysis of Categorical Data
ISBN: 364278819X ISBN-13(EAN): 9783642788192
Издательство: Springer
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Цена: 15372.00 р.
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Описание: The aim of this book is to give an up to date account of the most commonly uses statisti- cal models for categorical data. In many cases, the data sets are those data sets, which were not included in the examples of the book, although they at one point in time were regarded as potential can- didates for an example.

Classification and Knowledge Organization

Автор: R?diger Klar; Otto Opitz
Название: Classification and Knowledge Organization
ISBN: 3540629815 ISBN-13(EAN): 9783540629818
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Large collections of data and information necessitate adequate methods for their analysis. The book presents such methods, proposes and discusses recent approaches and implementations and describes a series of practical applications.

Regional Performance Measurement and Improvement

Автор: Soushi Suzuki; Peter Nijkamp
Название: Regional Performance Measurement and Improvement
ISBN: 9811091145 ISBN-13(EAN): 9789811091148
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This is the first book to fully introduce a newly developed distance friction minimization (DFM) model, which is one of the new efficiency improvement projection approaches in data envelopment analysis (DEA).

Introduction to the Theory and Application of Data Envelopment Analysis

Автор: Emmanuel Thanassoulis
Название: Introduction to the Theory and Application of Data Envelopment Analysis
ISBN: 1461355389 ISBN-13(EAN): 9781461355380
Издательство: Springer
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Цена: 27950.00 р.
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Описание: 1 DATA ENVELOPMENT ANALYSIS Data Envelopment Analysis (DEA) was initially developed as a method for assessing the comparative efficiencies of organisational units such as the branches of a bank, schools, hospital departments or restaurants.

Nonlinear Time Series Analysis of Economic and Financial Data

Автор: Philip Rothman
Название: Nonlinear Time Series Analysis of Economic and Financial Data
ISBN: 1461373344 ISBN-13(EAN): 9781461373346
Издательство: Springer
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Цена: 41925.00 р.
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Описание: Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade.

Analyzing and Modeling Data and Knowledge

Автор: Martin Schader
Название: Analyzing and Modeling Data and Knowledge
ISBN: 3540547088 ISBN-13(EAN): 9783540547082
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This volume encapsulates the papers presented at a conference on the classification of data held in 1991. The material is organized in three parts - data analysis and classification, data modelling and knowledge processing and applications and special subjects.


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