Large Data Sets And Nonlinearity
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Nonlinear Forecasting Using Large Datasets
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Author : Alessandro Giovannelli
language : en
Publisher:
Release Date : 2014
Nonlinear Forecasting Using Large Datasets written by Alessandro Giovannelli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
The primary objective of this paper is to propose two nonlinear extensions for macroeconomic forecasting using large datasets. First, we propose an alternative technique for factor estimation, i.e., kernel principal component analysis, which allows the factors to have a nonlinear relationship to the input variables. Second, we propose arti ficial neural networks as an alternative to the factor augmented linear forecasting equation. These two extensions allow us to determine whether, in general, there is empirical evidence in favor of nonlinear methods and, in particular, to verify whether the nonlinearity occurs in the estimation of the factors or in the functional form that links the target variable to the factors. In an e ffort to verify the empirical performances of the methods proposed, we conducted several pseudo forecasting exercises on the industrial production index and consumer price index for the Euro area and US economies. These methods were employed to construct the forecasts at 1-, 3-, 6-, and 12-month horizons using a large dataset containing 259 predictors for the Euro area and 131 predictors for the US economy. The results obtained from the empirical study suggest that the estimation of nonlinear factors, using kernel principal components, signifi cantly improves the quality of forecasts compared to the linear method, while the results for artifi cial neural networks have the same forecasting ability as the factor augmented linear forecasting equation.
Large Data Sets And Nonlinearity
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Author : Hyeyoen Kim
language : en
Publisher:
Release Date : 2009
Large Data Sets And Nonlinearity written by Hyeyoen Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Nonlinear Functional Projections For Clustering Of Highly Intertwining Large Datasets With Applications In Financial And Genomic Pattern Analysis
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Author : Hongmei Cui
language : en
Publisher:
Release Date : 2002
Nonlinear Functional Projections For Clustering Of Highly Intertwining Large Datasets With Applications In Financial And Genomic Pattern Analysis written by Hongmei Cui and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Cluster analysis categories.
Big Data Analytics With Matlab
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Author : L. Marvin
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-09-10
Big Data Analytics With Matlab written by L. Marvin and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-10 with categories.
MATLAB has the tools to work with large datasets and apply the necessary data analysis techniques. This book develops the work with nonlinear regression analysis techniques. Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today's technology, it's possible to analyze your data and get answers from it almost immediately - an effort that's slower and less efficient with more traditional business intelligence solutions. Nonlinear Regression models describe the nonlinear relationship between a response (output) variable, and one or more predictor (input) variables. Statistics and Machine Learning Toolbox allows you to fit linear, generalized linear, and nonlinear regression models, including stepwise models and mixed-effects models. Once you fit a model, you can use it to predict or simulate responses, assess the model fit using hypothesis tests, or use plots to visualize diagnostics, residuals, and interaction effects. Statistics and Machine Learning Toolbox also provides nonparametric regression methods to accommodate more complex regression curves without specifying the relationship between the response and the predictors with a predetermined regression function. You can predict responses for new data using the trained model. Gaussian process regression models also enable you to compute prediction intervals.
Nonlinear Time Series Analysis
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Author : Ruey S. Tsay
language : en
Publisher:
Release Date : 2018
Nonlinear Time Series Analysis written by Ruey S. Tsay and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with MATHEMATICS categories.
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors'noted experts in the field'explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: -''' Offers research developed by leading scholars of time series analysis -''' Presents R commands making it possible to reproduce all the analyses included in the text -''' Contains real-world examples throughout the book -''' Recommends exercises to test understanding of material presented -''' Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.'
Advanced Statistical Methods For The Analysis Of Large Data Sets
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Author : Agostino Di Ciaccio
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05
Advanced Statistical Methods For The Analysis Of Large Data Sets written by Agostino Di Ciaccio 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 2012-03-05 with Mathematics categories.
The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”
Nonlinear Dynamical Systems Analysis For The Behavioral Sciences Using Real Data
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Author : Stephen J. Guastello
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Nonlinear Dynamical Systems Analysis For The Behavioral Sciences Using Real Data written by Stephen J. Guastello and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
Although its roots can be traced to the 19th century, progress in the study of nonlinear dynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflect
Nonlinear Modeling And Forecasting
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Author : Martin Casdagli
language : en
Publisher: Westview Press
Release Date : 1992-06-20
Nonlinear Modeling And Forecasting written by Martin Casdagli and has been published by Westview Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-20 with Science categories.
System Modeling And Optimization Xx
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Author : E.W. Sachs
language : en
Publisher: Springer
Release Date : 2013-03-14
System Modeling And Optimization Xx written by E.W. Sachs and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Technology & Engineering categories.
System Modeling and Optimization XX deals with new developments in the areas of optimization, optimal control and system modeling. The themes range across various areas of optimization: continuous and discrete, numerical and analytical, finite and infinite dimensional, deterministic and stochastic, static and dynamic, theory and applications, foundations and case studies. Besides some classical topics, modern areas are also presented in the contributions, including robust optimization, filter methods, optimization of power networks, data mining and risk control. This volume contains invited and selected papers from presentations at the 20th IFIP TC7 Conference on System Modeling and Optimization, which took place at the University of Trier, Germany from July 23 to 27, 2001, and which was sponsored by the International Federation for Information Processing (IFIP).
Multiple Model Approaches To Nonlinear Modelling And Control
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Author : R Murray-Smith
language : en
Publisher: CRC Press
Release Date : 2020-11-26
Multiple Model Approaches To Nonlinear Modelling And Control written by R Murray-Smith and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-26 with Technology & Engineering categories.
This work presents approaches to modelling and control problems arising from conditions of ever increasing nonlinearity and complexity. It prescribes an approach that covers a wide range of methods being combined to provide multiple model solutions. Many component methods are described, as well as discussion of the strategies available for building a successful multiple model approach.