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Anglický jazyk
Time Series Analysis and Forecasting using Python & R
Autor: Jeffrey Strickland
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... Viac o knihe
Na objednávku, dodanie 2-4 týždne
103.14 €
bežná cena: 114.60 €
O knihe
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.
- Vydavateľstvo: Lulu.com
- Rok vydania: 2020
- Formát: Hardback
- Rozmer: 235 x 157 mm
- Jazyk: Anglický jazyk
- ISBN: 9781716451133
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