Time Series Models
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Forecasting Principles And Practice
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Author : Rob J Hyndman
language : en
Publisher: OTexts
Release Date : 2018-05-08
Forecasting Principles And Practice written by Rob J Hyndman and has been published by OTexts this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Business & Economics categories.
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.
Time Series
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Author : Raquel Prado
language : en
Publisher: CRC Press
Release Date : 2010-05-21
Time Series written by Raquel Prado and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-21 with Mathematics categories.
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.
Time Series Models For Business And Economic Forecasting
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Author : Philip Hans Franses
language : en
Publisher: Cambridge University Press
Release Date : 1998-10-15
Time Series Models For Business And Economic Forecasting written by Philip Hans Franses 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 1998-10-15 with Business & Economics categories.
The econometric analysis of economic and business time series is a major field of research and application. The last few decades have witnessed an increasing interest in both theoretical and empirical developments in constructing time series models and in their important application in forecasting. In Time Series Models for Business and Economic Forecasting, Philip Franses examines recent developments in time series analysis. The early parts of the book focus on the typical features of time series data in business and economics. Part III is concerned with the discussion of some important concepts in time series analysis, the discussion focuses on the techniques which can be readily applied in practice. Parts IV-VIII suggest different modeling methods and model structures. Part IX extends the concepts in chapter three to multivariate time series. Part X examines common aspects across time series.
Bayesian Time Series Models
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Author : David Barber
language : en
Publisher: Cambridge University Press
Release Date : 2011-08-11
Bayesian Time Series Models written by David Barber 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 2011-08-11 with Computers categories.
The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Multiple Time Series Models
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Author : Patrick T. Brandt
language : en
Publisher: SAGE
Release Date : 2007
Multiple Time Series Models written by Patrick T. Brandt and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
Many analyses of time series data involve multiple, related variables. Multiple Time Series Models presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available.Key Features Offers a detailed comparison of different time series methods and approaches. Includes a self-contained introduction to vector autoregression modeling. Situates multiple time series modeling as a natural extension of commonly taught statistical models.
Time Series Models
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Author : Andrew C. Harvey
language : en
Publisher: Financial Times/Prentice Hall
Release Date : 1993
Time Series Models written by Andrew C. Harvey and has been published by Financial Times/Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Time-series analysis categories.
A companion volume to The Econometric Analysis of Time series, this book focuses on the estimation, testing and specification of dynamic models which are not based on any behavioural theory. It covers univariate and multivariate time series and emphasizes autoregressive moving-average processes.
Forecasting Structural Time Series Models And The Kalman Filter
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Author : Andrew C. Harvey
language : en
Publisher: Cambridge University Press
Release Date : 1990
Forecasting Structural Time Series Models And The Kalman Filter written by Andrew C. Harvey 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 1990 with Business & Economics categories.
A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.
Modelling Financial Time Series
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Author : Stephen J. Taylor
language : en
Publisher: World Scientific
Release Date : 2008
Modelling Financial Time Series written by Stephen J. Taylor and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.
This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts.This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends.
Practical Time Series Analysis
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Author : Aileen Nielsen
language : en
Publisher: O'Reilly Media
Release Date : 2019-09-20
Practical Time Series Analysis written by Aileen Nielsen and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance