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Könyv Time Series Analysis and Forecasting using Python & R Jeffrey Strickland

Time Series Analysis and Forecasting using Python & R

Szerző: Jeffrey Strickland
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Lulu.com
Elérhetőség: 50 % esély
Keressük az egész világon
32 713 Ft
This book full-color textbook assumes a basic understanding of statistics and mathematical or statis...

Információk a könyvről

Szerző
Jeffrey Strickland
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2020
oldal
448
EAN
9781716451133
ISBN
1716451132
Enbook ID
33555638
Kiadó
Lulu.com
Súly
767
Méretek
152 x 229 x 25

Teljes leírás

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.

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