Introduction to Time Series Analysis and Forecasting

Download or Read eBook Introduction to Time Series Analysis and Forecasting PDF written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle.
Introduction to Time Series Analysis and Forecasting
Author :
Publisher : John Wiley & Sons
Total Pages : 670
Release :
ISBN-10 : 9781118745151
ISBN-13 : 1118745159
Rating : 4/5 (51 Downloads)

Book Synopsis Introduction to Time Series Analysis and Forecasting by : Douglas C. Montgomery

Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.


Introduction to Time Series Analysis and Forecasting Related Books

Introduction to Time Series Analysis and Forecasting
Language: en
Pages: 670
Authors: Douglas C. Montgomery
Categories: Mathematics
Type: BOOK - Published: 2015-04-21 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics an
Introduction to Time Series and Forecasting
Language: en
Pages: 429
Authors: Peter J. Brockwell
Categories: Mathematics
Type: BOOK - Published: 2013-03-14 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

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 knowled
Forecasting: principles and practice
Language: en
Pages: 380
Authors: Rob J Hyndman
Categories: Business & Economics
Type: BOOK - Published: 2018-05-08 - Publisher: OTexts

DOWNLOAD EBOOK

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic
Introduction to Time Series Analysis
Language: en
Pages: 233
Authors: Mark Pickup
Categories: Social Science
Type: BOOK - Published: 2014-10-15 - Publisher: SAGE Publications

DOWNLOAD EBOOK

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 f
Introduction to Time Series Using Stata
Language: en
Pages: 446
Authors: Sean Becketti
Categories: Mathematical statistics
Type: BOOK - Published: 2020-03-02 - Publisher:

DOWNLOAD EBOOK

Introduction to Time Series Using Stata, Revised Edition, by Sean Becketti, is a practical guide to working with time-series data using Stata. In this book, Bec