Practical Time Series Forecasting with R

Name: Practical Time Series Forecasting with R
Brand: Storyfire Ltd
SKU: 9780997847949
Price: 731 CZK
Availability: InStock

Autor: Galit Shmueli

Jazyk:

Vazba: Brožovaná

Vydavatel: Storyfire Ltd

Dostupnost: Skladem u dodavatele

Odesíláme za 14-21 dnů

731 Kč

Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition provides an applied approa...

Informace o knize

Autor

Galit Shmueli

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2024

Stránek

252

EAN

9780997847949

ISBN

0997847948

Enbook ID

45216541

Vydavatel

Storyfire Ltd

Hmotnost

445

Rozměry

178 x 254 x 13

Kompletní popis

Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications.

The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time series data.

This edition features the R fable package, full color, enhanced organization, and new material. It includes:

Popular forecasting methods including smoothing algorithms, regression models, ARIMA, neural networks, deep learning, and ensembles
A practical approach to evaluating the performance of forecasting solutions
A business-analytics exposition focused on linking time-series forecasting to business goals
Guided cases for integrating the acquired knowledge using real data
End-of-chapter problems to facilitate active learning
Data, R code, and instructor materials on companion website
Affordable and globally-available textbook, available in hardcover, paperback, and Kindle formats

Practical Time Series Forecasting with R: A Hands-On Guide, Third Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, information systems, finance, and management.

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