Juana Sanchez (Los Angeles University of California)

Time Series for Data Scientists

Data Management, Description, Modeling and Forecasting

• Gebundenes Buch

Produktbeschreibung

Learn by doing with this guide to classical and contemporary machine learning approaches to time series data analysis. With data sets, commented R programs, case studies and quizzes, this is an essential and accessible resource for undergraduate and graduate students in statistics and data science, and researchers in data-rich disciplines.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 550
• Erscheinungstermin: 11. Mai 2023
• Englisch
• Abmessung: 248mm x 176mm x 27mm
• Gewicht: 1026g
• ISBN-13: 9781108837774
• ISBN-10: 1108837778
• Artikelnr.: 66996535

Autorenporträt

Juana Sanchez is Senior Lecturer in Statistics at the University of California, Los Angeles. She is Editor of the Datasets and Stories section of the ASA's Journal of Statistics and Data Science Education and is the author of Probability for Data Scientists (2020).

Inhaltsangabe

Part I. Descriptive Features of Time Series Data: 1. Introduction to time series data
2. Smoothing and decomposing a time series
3. Summary statistics of stationary time series
Part II. Univariate Models of Temporal Dependence: 4. The algebra of differencing and backshifting
5. Stationary stochastic processes
6. ARIMA(p,d,q)(P,D,Q)$_F$ modeling and forecasting
Part III. Multivariate Modeling and Forecasting: 7. Latent process models for time series
8. Vector autoregression
9. Classical regression with ARMA residuals
10. Machine learning methods for time series
References
Index.