Proceedings of the Pacific Rim Statistical Conference for Production Engineering Big Data, Production Engineering and Statistics /

This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016. The papers included discuss a wide range of statistical chall...

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Médium: Elektronický zdroj E-kniha
Jazyk:English
Vydavateľské údaje: Singapore : Springer Singapore , 2018.
Vydanie:1st ed. 2018.
Edícia:ICSA Book Series in Statistics,
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ISBN:9789811081682
ISSN:2199-0980
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245 1 0 |a Proceedings of the Pacific Rim Statistical Conference for Production Engineering  |h [electronic resource] :  |b Big Data, Production Engineering and Statistics /  |c edited by Dongseok Choi, Daeheung Jang, Tze Leung Lai, Youngjo Lee, Ying Lu, Jun Ni, Peter Qian, Peihua Qiu, George Tiao. 
250 |a 1st ed. 2018. 
260 1 |a Singapore :  |b Springer Singapore ,  |c 2018. 
300 |a VIII, 170 p. 36 illus., 29 illus. in color.  |b online resource. 
490 1 |a ICSA Book Series in Statistics,  |x 2199-0980 
500 |a Mathematics and Statistics  
505 0 |a Section 1: Design and Collection of Big Data -- Section 2: Analytic Methods of Big Data -- Section 3: Operation/Production Decision Making -- Section 4 Reliability and Health Management.-Section 5: Statistical Theories Related with the Big Data -- Section 6: Recent Advances in Statistical Methods -- Section 7: Development of Statistical Software for the Big Data -- Section 8: Big Data and Its Application to Industry -- Section 9: Big Data and Its Application to Industry. 
516 |a text file PDF 
520 |a This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016. The papers included discuss a wide range of statistical challenges, methods and applications for big data in production engineering, and introduce recent advances in relevant statistical methods. 
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650 0 |a Big data. 
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