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 ...
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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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Add this copy of Time Series Analysis and Forecasting Using Python & R to cart. $55.11, good condition, Sold by Goodwill of Greater Milwaukee rated 5.0 out of 5 stars, ships from Milwaukee, WI, UNITED STATES, published 2020 by Lulu. com.
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Book is considered to be in good or better condition. The actual cover image may not match the stock photo. Hard cover books may show signs of wear on the spine cover or dust jacket. Paperback book may show signs of wear on spine or cover as well as having a slight bend curve or creasing to it. Book should have minimal to no writing inside and no highlighting. Pages should be free of tears or creasing. Stickers should not be present on cover or elsewhere and any CD or DVD expected with the book is included. Book is not a former library copy.
Add this copy of Time Series Analysis and Forecasting Using Python & R to cart. $108.73, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Santa Clarita, CA, UNITED STATES, published 2020 by Lulu. com.
