Estimation Of Parameters In Integrated Autoregressive Moving Average Time Series Models Part 1 Autoregressive Models

Download Estimation Of Parameters In Integrated Autoregressive Moving Average Time Series Models Part 1 Autoregressive Models full books in PDF, epub, and Kindle. Read online Estimation Of Parameters In Integrated Autoregressive Moving Average Time Series Models Part 1 Autoregressive Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Time Series Analysis Univariate and Multivariate Methods

Author : William W. S. Wei
Publisher : Pearson
ISBN 13 : 9780134995366
Total Pages : 648 pages
Book Rating : 4.9/5 (953 download)

DOWNLOAD NOW!

Book Synopsis Time Series Analysis Univariate and Multivariate Methods by : William W. S. Wei

Download or read book Time Series Analysis Univariate and Multivariate Methods written by William W. S. Wei and published by Pearson. This book was released on 2018-03-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.

Introduction to Time Series and Forecasting

Author : Peter J. Brockwell
Publisher : Springer Science & Business Media
ISBN 13 : 1475725264
Total Pages : 429 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell

Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Forecasting: principles and practice

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

DOWNLOAD NOW!

Book Synopsis Forecasting: principles and practice by : Rob J Hyndman

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Time Series Analysis

Author : Mark Pickup
Publisher : SAGE Publications
ISBN 13 : 1483313115
Total Pages : 233 pages
Book Rating : 4.4/5 (833 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Time Series Analysis by : Mark Pickup

Download or read book Introduction to Time Series Analysis written by Mark Pickup and published by SAGE Publications. This book was released on 2014-10-15 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University

Time-Series Forecasting

Author : Chris Chatfield
Publisher : CRC Press
ISBN 13 : 1420036203
Total Pages : 281 pages
Book Rating : 4.4/5 (2 download)

DOWNLOAD NOW!

Book Synopsis Time-Series Forecasting by : Chris Chatfield

Download or read book Time-Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space

Random Coefficient Autoregressive Models: An Introduction

Author : D.F. Nicholls
Publisher : Springer Science & Business Media
ISBN 13 : 1468462733
Total Pages : 160 pages
Book Rating : 4.4/5 (684 download)

DOWNLOAD NOW!

Book Synopsis Random Coefficient Autoregressive Models: An Introduction by : D.F. Nicholls

Download or read book Random Coefficient Autoregressive Models: An Introduction written by D.F. Nicholls and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph we have considered a class of autoregressive models whose coefficients are random. The models have special appeal among the non-linear models so far considered in the statistical literature, in that their analysis is quite tractable. It has been possible to find conditions for stationarity and stability, to derive estimates of the unknown parameters, to establish asymptotic properties of these estimates and to obtain tests of certain hypotheses of interest. We are grateful to many colleagues in both Departments of Statistics at the Australian National University and in the Department of Mathematics at the University of Wo110ngong. Their constructive criticism has aided in the presentation of this monograph. We would also like to thank Dr M. A. Ward of the Department of Mathematics, Australian National University whose program produced, after minor modifications, the "three dimensional" graphs of the log-likelihood functions which appear on pages 83-86. Finally we would like to thank J. Radley, H. Patrikka and D. Hewson for their contributions towards the typing of a difficult manuscript. IV CONTENTS CHAPTER 1 INTRODUCTION 1. 1 Introduction 1 Appendix 1. 1 11 Appendix 1. 2 14 CHAPTER 2 STATIONARITY AND STABILITY 15 2. 1 Introduction 15 2. 2 Singly-Infinite Stationarity 16 2. 3 Doubly-Infinite Stationarity 19 2. 4 The Case of a Unit Eigenvalue 31 2. 5 Stability of RCA Models 33 2. 6 Strict Stationarity 37 Appendix 2. 1 38 CHAPTER 3 LEAST SQUARES ESTIMATION OF SCALAR MODELS 40 3.

Data Science

Author : Vijay Kotu
Publisher : Morgan Kaufmann
ISBN 13 : 0128147628
Total Pages : 570 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Data Science by : Vijay Kotu

Download or read book Data Science written by Vijay Kotu and published by Morgan Kaufmann. This book was released on 2018-11-27 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: - Gain the necessary knowledge of different data science techniques to extract value from data. - Master the concepts and inner workings of 30 commonly used powerful data science algorithms. - Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... - Contains fully updated content on data science, including tactics on how to mine business data for information - Presents simple explanations for over twenty powerful data science techniques - Enables the practical use of data science algorithms without the need for programming - Demonstrates processes with practical use cases - Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language - Describes the commonly used setup options for the open source tool RapidMiner

Theory and Methods of Statistics

Author : P.K. Bhattacharya
Publisher : Academic Press
ISBN 13 : 0128041234
Total Pages : 546 pages
Book Rating : 4.1/5 (28 download)

DOWNLOAD NOW!

Book Synopsis Theory and Methods of Statistics by : P.K. Bhattacharya

Download or read book Theory and Methods of Statistics written by P.K. Bhattacharya and published by Academic Press. This book was released on 2016-06-23 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. - Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource - Serves as an excellent text for select master's and PhD programs, as well as a professional reference - Integrates numerous examples to illustrate advanced concepts - Includes many probability inequalities useful for investigating convergence of statistical procedures

Handbook of Statistical Analysis and Data Mining Applications

Author : Ken Yale
Publisher : Elsevier
ISBN 13 : 0124166458
Total Pages : 824 pages
Book Rating : 4.1/5 (241 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Statistical Analysis and Data Mining Applications by : Ken Yale

Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Ken Yale and published by Elsevier. This book was released on 2017-11-09 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Introduction to Time Series Forecasting With Python

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 359 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis Introduction to Time Series Forecasting With Python by : Jason Brownlee

Download or read book Introduction to Time Series Forecasting With Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2017-02-16 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series forecasting is different from other machine learning problems. The key difference is the fixed sequence of observations and the constraints and additional structure this provides. In this Ebook, finally cut through the math and specialized methods for time series forecasting. Using clear explanations, standard Python libraries and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement forecasting models for time series data.

Statistical Postprocessing of Ensemble Forecasts

Author : Stéphane Vannitsem
Publisher : Elsevier
ISBN 13 : 012812248X
Total Pages : 364 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Statistical Postprocessing of Ensemble Forecasts by : Stéphane Vannitsem

Download or read book Statistical Postprocessing of Ensemble Forecasts written by Stéphane Vannitsem and published by Elsevier. This book was released on 2018-05-17 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner

Connecting Medical Informatics and Bio-informatics

Author : Rolf Engelbrecht
Publisher : IOS Press
ISBN 13 : 1586035495
Total Pages : 1052 pages
Book Rating : 4.5/5 (86 download)

DOWNLOAD NOW!

Book Synopsis Connecting Medical Informatics and Bio-informatics by : Rolf Engelbrecht

Download or read book Connecting Medical Informatics and Bio-informatics written by Rolf Engelbrecht and published by IOS Press. This book was released on 2005 with total page 1052 pages. Available in PDF, EPUB and Kindle. Book excerpt: A variety of topics of bio-informatics, including both medical and bio-medical informatics are addressed by MIE. The main theme in this publication is the development of connections between bio-informatics and medical informatics. Tools and concepts from both disciplines can complement each other.

U.S. Geological Survey Water-supply Paper

Author :
Publisher :
ISBN 13 :
Total Pages : 542 pages
Book Rating : 4.:/5 (319 download)

DOWNLOAD NOW!

Book Synopsis U.S. Geological Survey Water-supply Paper by :

Download or read book U.S. Geological Survey Water-supply Paper written by and published by . This book was released on 1982 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Wireless Network Traffic and Quality of Service Support: Trends and Standards

Author : Lagkas, Thomas D.
Publisher : IGI Global
ISBN 13 : 1615207724
Total Pages : 571 pages
Book Rating : 4.6/5 (152 download)

DOWNLOAD NOW!

Book Synopsis Wireless Network Traffic and Quality of Service Support: Trends and Standards by : Lagkas, Thomas D.

Download or read book Wireless Network Traffic and Quality of Service Support: Trends and Standards written by Lagkas, Thomas D. and published by IGI Global. This book was released on 2010-03-31 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers cutting edge approaches for the provision of quality of service in wireless local area networks"--Provided by publisher.

Large Scale Networks

Author : Radu Dobrescu
Publisher : CRC Press
ISBN 13 : 1498750184
Total Pages : 302 pages
Book Rating : 4.4/5 (987 download)

DOWNLOAD NOW!

Book Synopsis Large Scale Networks by : Radu Dobrescu

Download or read book Large Scale Networks written by Radu Dobrescu and published by CRC Press. This book was released on 2016-10-03 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction. Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history.

Advances in data-driven approaches and modeling of complex systems

Author : Mohd Hafiz Mohd
Publisher : Frontiers Media SA
ISBN 13 : 2832526659
Total Pages : 133 pages
Book Rating : 4.8/5 (325 download)

DOWNLOAD NOW!

Book Synopsis Advances in data-driven approaches and modeling of complex systems by : Mohd Hafiz Mohd

Download or read book Advances in data-driven approaches and modeling of complex systems written by Mohd Hafiz Mohd and published by Frontiers Media SA. This book was released on 2023-06-27 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Oxford Handbook of Credit Derivatives

Author : Alexander Lipton
Publisher : OUP Oxford
ISBN 13 : 0191648248
Total Pages : 704 pages
Book Rating : 4.1/5 (916 download)

DOWNLOAD NOW!

Book Synopsis The Oxford Handbook of Credit Derivatives by : Alexander Lipton

Download or read book The Oxford Handbook of Credit Derivatives written by Alexander Lipton and published by OUP Oxford. This book was released on 2013-01-17 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the late 1990s, the spectacular growth of a secondary market for credit through derivatives has been matched by the emergence of mathematical modelling analysing the credit risk embedded in these contracts. This book aims to provide a broad and deep overview of this modelling, covering statistical analysis and techniques, modelling of default of both single and multiple entities, counterparty risk, Gaussian and non-Gaussian modelling, and securitisation. Both reduced-form and firm-value models for the default of single entities are considered in detail, with extensive discussion of both their theoretical underpinnings and practical usage in pricing and risk. For multiple entity modelling, the now notorious Gaussian copula is discussed with analysis of its shortcomings, as well as a wide range of alternative approaches including multivariate extensions to both firm-value and reduced form models, and continuous-time Markov chains. One important case of multiple entities modelling - counterparty risk in credit derivatives - is further explored in two dedicated chapters. Alternative non-Gaussian approaches to modelling are also discussed, including extreme-value theory and saddle-point approximations to deal with tail risk. Finally, the recent growth in securitisation is covered, including house price modelling and pricing models for asset-backed CDOs. The current credit crisis has brought modelling of the previously arcane credit markets into the public arena. Lipton and Rennie with their excellent team of contributors, provide a timely discussion of the mathematical modelling that underpins both credit derivatives and securitisation. Though technical in nature, the pros and cons of various approaches attempt to provide a balanced view of the role that mathematical modelling plays in the modern credit markets. This book will appeal to students and researchers in statistics, economics, and finance, as well as practitioners, credit traders, and quantitative analysts