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Synopsis
This book provides a comparison of different forecasting methods with special implementations for different time series data and evaluates the results of forecasting experiments. It is important for the selected forecasting method to give more accurate results and smaller forecast errors. Also, the coding and the implementation processes have an effect in choosing a forecasting method. The first chapter explains forecasting, the second chapter gives information about the forecasting process, the third chapter gives examples of the forecasting methods used in the literature. The explanation of forecasting methods begins with the fourth chapter with the explanation of the so called “naive method”. The fifth chapter explains time series regression methods, the sixth chapter presents exponential smoothing methods, the seventh chapter gives information about the (S)ARIMA method. The eight chapter explains the implementation of these forecasting methods written on R program.The experiments evaluating these forecasting methods are introduced and explained in the ninth chapter. Finally, a general overview and comparison of the methods is presented.
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Présentation de l'éditeur
This book provides a comparison of different forecasting methods with special implementations for different time series data and evaluates the results of forecasting experiments. It is important for the selected forecasting method to give more accurate results and smaller forecast errors. Also, the coding and the implementation processes have an effect in choosing a forecasting method. The first chapter explains forecasting, the second chapter gives information about the forecasting process, the third chapter gives examples of the forecasting methods used in the literature. The explanation of forecasting methods begins with the fourth chapter with the explanation of the so called “naive method”. The fifth chapter explains time series regression methods, the sixth chapter presents exponential smoothing methods, the seventh chapter gives information about the (S)ARIMA method. The eight chapter explains the implementation of these forecasting methods written on R program.The experiments evaluating these forecasting methods are introduced and explained in the ninth chapter. Finally, a general overview and comparison of the methods is presented.
Biographie de l'auteur
Dr. Özge Tuğrul Sönmez has graduated from İstanbul Technical University with Bachelors degree in Industrial Engineering in 2008. She has received Master of Science degree in Industrial Engineering from Boğaziçi University in 2010 and PHD degree from İstanbul Technical University in Industrial Engineering in 2016.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurLAP LAMBERT Academic Publishing
- Date d'édition2017
- ISBN 10 3330031786
- ISBN 13 9783330031784
- ReliureBroché
- Langueanglais
- Nombre de pages264
- Coordonnées du fabricantnon disponible
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Methods for Time Series Forecasting
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330031786
ISBN 13 : 9783330031784
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 159137558
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Methods for Time Series Forecasting : with Applications in R
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330031786
ISBN 13 : 9783330031784
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a comparison of different forecasting methods with special implementations for different time series data and evaluates the results of forecasting experiments. It is important for the selected forecasting method to give more accurate results and smaller forecast errors. Also, the coding and the implementation processes have an effect in choosing a forecasting method. The first chapter explains forecasting, the second chapter gives information about the forecasting process, the third chapter gives examples of the forecasting methods used in the literature. The explanation of forecasting methods begins with the fourth chapter with the explanation of the so called 'naive method'. The fifth chapter explains time series regression methods, the sixth chapter presents exponential smoothing methods, the seventh chapter gives information about the (S)ARIMA method. The eight chapter explains the implementation of these forecasting methods written on R program.The experiments evaluating these forecasting methods are introduced and explained in the ninth chapter. Finally, a general overview and comparison of the methods is presented. N° de réf. du vendeur 9783330031784
Quantité disponible : 1 disponible(s)
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Methods for Time Series Forecasting
Edité par
LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10 : 3330031786
ISBN 13 : 9783330031784
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -This book provides a comparison of different forecasting methods with special implementations for different time series data and evaluates the results of forecasting experiments. It is important for the selected forecasting method to give more accurate results and smaller forecast errors. Also, the coding and the implementation processes have an effect in choosing a forecasting method. The first chapter explains forecasting, the second chapter gives information about the forecasting process, the third chapter gives examples of the forecasting methods used in the literature. The explanation of forecasting methods begins with the fourth chapter with the explanation of the so called ¿naive method¿. The fifth chapter explains time series regression methods, the sixth chapter presents exponential smoothing methods, the seventh chapter gives information about the (S)ARIMA method. The eight chapter explains the implementation of these forecasting methods written on R program.The experiments evaluating these forecasting methods are introduced and explained in the ninth chapter. Finally, a general overview and comparison of the methods is presented.Books on Demand GmbH, Überseering 33, 22297 Hamburg 264 pp. Englisch. N° de réf. du vendeur 9783330031784
Quantité disponible : 2 disponible(s)
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Methods for Time Series Forecasting: with Applications in R
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330031786
ISBN 13 : 9783330031784
Neuf
Paperback
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. 264 pages. 8.66x5.91x0.60 inches. In Stock. N° de réf. du vendeur 3330031786
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Image d'archives
Methods for Time Series Forecasting: with Applications in R
Edité par
LAP LAMBERT Academic Publishing, 2017
ISBN 10 : 3330031786
ISBN 13 : 9783330031784
Neuf
paperback
Vendeur : dsmbooks, Liverpool, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
paperback. Etat : New. New. book. N° de réf. du vendeur D8S0-3-M-3330031786-6
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