Контакт
Как се пазарува?
Доставка
Наръчник за пазаруване
Time Series Analysis and Forecasting using Python & R
Английски език
184 b
30 дни за връщане на стоката
Може би ще Ви заинтересува
/
С меки корици
21.10
€
41.27 лв
/
С твърди корици
26.84
€
52.50 лв
/
С меки корици
14.79
€
28.93 лв
/
С твърди корици
235.48
€
460.56 лв
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.
Информация за книгата
Английски език
