Advances in Time Series Data Methods in Applied Economic Research PDF Download
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Author: Nicholas Tsounis
Publisher: Springer
ISBN: 9783030021931
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
This conference proceedings volume presents advanced methods in time series estimation models that are applicable various areas of applied economic research such as international economics, macroeconomics, microeconomics, finance economics and agricultural economics. Featuring contributions presented at the 2018 International Conference on Applied Economics (ICOAE) held in Warsaw, Poland, this book presents contemporary research using applied econometric method for analysis as well as country specific studies with potential implications on economic policy. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics to analyse economic problems of the real world usually with economic policy interest. ICOAE is an annual conference started in 2008 with the aim to bring together economists from different fields of applied economic research in order to share methods and ideas. Approximately 150 papers are submitted each year from about 40 countries around the world. The goal of the conference and the enclosed papers is to allow for an exchange of experiences with different applied econometric methods and to promote joint initiatives among well-established economic fields such as finance, agricultural economics, health economics, education economics, international trade theory and management and marketing strategies. Featuring global contributions, this book will be of interest to researchers, academics, professionals and policy makers in the field of applied economics and econometrics.
Author: Nicholas Tsounis
Publisher: Springer
ISBN: 9783030021931
Category : Business & Economics
Languages : en
Pages : 0
Get Book Here
Book Description
This conference proceedings volume presents advanced methods in time series estimation models that are applicable various areas of applied economic research such as international economics, macroeconomics, microeconomics, finance economics and agricultural economics. Featuring contributions presented at the 2018 International Conference on Applied Economics (ICOAE) held in Warsaw, Poland, this book presents contemporary research using applied econometric method for analysis as well as country specific studies with potential implications on economic policy. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics to analyse economic problems of the real world usually with economic policy interest. ICOAE is an annual conference started in 2008 with the aim to bring together economists from different fields of applied economic research in order to share methods and ideas. Approximately 150 papers are submitted each year from about 40 countries around the world. The goal of the conference and the enclosed papers is to allow for an exchange of experiences with different applied econometric methods and to promote joint initiatives among well-established economic fields such as finance, agricultural economics, health economics, education economics, international trade theory and management and marketing strategies. Featuring global contributions, this book will be of interest to researchers, academics, professionals and policy makers in the field of applied economics and econometrics.
Author: Björn Schelter
Publisher: John Wiley & Sons
ISBN: 3527609512
Category : Science
Languages : en
Pages : 514
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Book Description
This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest developments will profit from this handbook.
Author: Ajoy K. Palit
Publisher: Springer Science & Business Media
ISBN: 1846281849
Category : Computers
Languages : en
Pages : 382
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Book Description
Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.
Author: Randal Douc
Publisher: CRC Press
ISBN: 1466502347
Category : Mathematics
Languages : en
Pages : 548
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Book Description
This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.
Author: Tata Subba Rao
Publisher: Elsevier
ISBN: 0444538585
Category : Mathematics
Languages : en
Pages : 778
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Book Description
'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.
Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Chun-Kit Ngan
Publisher: BoD – Books on Demand
ISBN: 1789847788
Category : Mathematics
Languages : en
Pages : 131
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Book Description
This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting and classification, data analytics, machine learning, deep learning, and artificial intelligence.
Author: I. Gusti Ngurah Agung
Publisher: John Wiley & Sons
ISBN: 1119504716
Category : Mathematics
Languages : en
Pages : 538
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Book Description
Introduces the latest developments in forecasting in advanced quantitative data analysis This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable. Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers. Presents models that are all classroom tested Contains real-life data samples Contains over 350 equation specifications of various time series models Contains over 200 illustrative examples with special notes and comments Applicable for time series data of all quantitative studies Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.
Author: Cagdas Hakan Aladag
Publisher: Bentham Science Publishers
ISBN: 1681085283
Category : Mathematics
Languages : en
Pages : 196
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Book Description
This volume is a valuable source of recent knowledge about advanced time series forecasting techniques such as artificial neural networks, fuzzy time series, or hybrid approaches. New forecasting frameworks are discussed and their application is demonstrated. The second volume of the series includes applications of some powerful forecasting approaches with a focus on fuzzy time series methods. Chapters integrate these methods with concepts such as neural networks, high order multivariate systems, deterministic trends, distance measurement and much more. The chapters are contributed by eminent scholars and serve to motivate and accelerate future progress while introducing new branches of time series forecasting. This book is a valuable resource for MSc and PhD students, academic personnel and researchers seeking updated and critically important information on the concepts of advanced time series forecasting and its applications.
Author: Peter J. Brockwell
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429
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Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
