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Englisch
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Beschreibung
"Learn by doing with this guide to classical and contemporary machine learning approaches to time series data analysis. With datasets, 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"--
"Learn by doing with this guide to classical and contemporary machine learning approaches to time series data analysis. With datasets, 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"--
Über den Autor
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).
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Allgemeines |
Genre: | Importe, Wirtschaft |
Rubrik: | Recht & Wirtschaft |
Medium: | Buch |
Inhalt: | Gebunden |
ISBN-13: | 9781108837774 |
ISBN-10: | 1108837778 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Sanchez, Juana |
Hersteller: | Cambridge University Press |
Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
Maße: | 248 x 176 x 27 mm |
Von/Mit: | Juana Sanchez |
Erscheinungsdatum: | 13.07.2023 |
Gewicht: | 1,018 kg |
Über den Autor
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).
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: | 2023 |
---|---|
Fachbereich: | Allgemeines |
Genre: | Importe, Wirtschaft |
Rubrik: | Recht & Wirtschaft |
Medium: | Buch |
Inhalt: | Gebunden |
ISBN-13: | 9781108837774 |
ISBN-10: | 1108837778 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Sanchez, Juana |
Hersteller: | Cambridge University Press |
Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
Maße: | 248 x 176 x 27 mm |
Von/Mit: | Juana Sanchez |
Erscheinungsdatum: | 13.07.2023 |
Gewicht: | 1,018 kg |
Sicherheitshinweis