Contact
How to shop
Delivery
Shopping guide
Time Series Analysis and Forecasting using Python & R
English
198 b
Delivery to Austria
Up to 30 days for returns
You might also be interested in
/
Hardback
23.49
€
/
Paperback
34.49
€
/
Paperback
6.39
€
/
Hardback
51.79
€
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.
About the book
English
Give this book today
It's easy
1 Add to cart and choose Deliver as present at the checkout 2 We'll send you a voucher 3 The book will arrive at the recipient's addressHi! I'm Libroamiko, your book advisor.
How can I help you?