Time Series Analysis And Forecasting Using Python And R(1st Edition)

Authors:

Jeffrey Strickland

Type:Hardcover/ PaperBack / Loose Leaf
Condition: Used/New

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Book details

ISBN: 1716451132, 978-1716451133

Book publisher: Lulu.com

Book Price $0 : This Book Full-color Textbook Assumes A Basic Understanding Of Statistics And Mathematical Or Statistical Modeling. Although A Little Programming Experience Would Be Nice, But It Is Not Required. We Use Current Real-world Data, Like COVID-19, To Motivate Times Series Analysis Have Three Thread Problems That Appear In Nearly Every Chapter: "Got Milk?", "Got A Job?" And "Where's The Beef?" Chapter 1: Loading Data In The R-Studio And Jupyter Notebook Environments. Chapter 2: Components Of A Times Series And Decomposition Chapter 3: Moving Averages (MAs) And COVID-19 Chapter 4: Simple Exponential Smoothing (SES), Holt's And Holt-Winter's Double And Triple Exponential Smoothing Chapter 5: Python Programming In Jupyter Notebook For The Concepts Covered In Chapters 2, 3 And 4 Chapter 6: Stationarity And Differencing, Including Unit Root Tests. Chapter 7: ARIMA And SARMIA (seasonal) Modeling And Forecast Development Chapter 8: ARIMA Modeling Using Python Chapter 9: Structural Models And Analysis Using Unobserved Component Models (UCMs) Chapter 10: Advanced Time Series Analysis, Including Time-series Interventions, Exogenous Regressors, And Vector Autoregressive (VAR) Processes.