Proceedings of the Pacific Rim Statistical Conference for Production Engineering

1. Front Matter

   Pages i-viii

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2. Design and Collection of Big Data

   1. Front Matter

      Pages 1-1

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   2. Bottom-Up Estimation and Top-Down Prediction: Solar Energy Prediction Combining Information from Multiple Sources

      • Youngdeok Hwang, Siyuan Lu, Jae-Kwang Kim

      Pages 3-14

   3. The 62% Problems of SN Ratio and New Conference Matrix for Optimization: To Reduce Experiment Numbers and to Increase Reliability for Optimization

      • Teruo Mori

      Pages 15-20

3. Analytic Methods of Big Data

   1. Front Matter

      Pages 21-21

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   2. Possible Clinical Use of Big Data: Personal Brain Connectomics

      • Dong Soo Lee

      Pages 23-31

   3. The Real-Time Tracking and Alarming the Early Neurological Deterioration Using Continuous Blood Pressure Monitoring in Patient with Acute Ischemic Stroke

      • Youngjo Lee, Maengseok Noh, Il Do Ha

      Pages 33-37

4. Operation/Production Decision Making

   1. Front Matter

      Pages 39-39

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   2. Condition Monitoring and Operational Decision-Making in Modern Semiconductor Manufacturing Systems

      • Dragan Djurdjanovic

      Pages 41-66

   3. Multistage Manufacturing Processes: Innovations in Statistical Modeling and Inference

      • Hsiang-Ling Hsu, Ching-Kang Ing, Tze Leung Lai, Shu-Hui Yu

      Pages 67-81

5. Reliability and Health Management

   1. Front Matter

      Pages 83-83

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   2. Recent Research in Dynamic Screening System for Sequential Process Monitoring

      • Peihua Qiu, Lu You

      Pages 85-93

   3. Degradation Analysis with Measurement Errors

      • Chien-Yu Peng, Hsueh-Fang Ai

      Pages 95-122

6. Recent Advances in Statistical Methods

   1. Front Matter

      Pages 123-123

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   2. A Least Squares Method for Detecting Multiple Change Points in a Univariate Time Series

      • Kyu S. Hahn, Won Son, Hyungwon Choi, Johan Lim

      Pages 125-143

   3. Detecting the Change of Variance by Using Conditional Distribution with Diverse Copula Functions

      • Jong-Min Kim, Jaiwook Baik, Mitch Reller

      Pages 145-154

   4. Clustering Methods for Spherical Data: An Overview and a New Generalization

      • Sungsu Kim, Ashis SenGupta

      Pages 155-164

   5. A Semiparametric Inverse Gaussian Model and Inference for Survival Data

      • Sangbum Choi

      Pages 165-170

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.

• Applied Statistics
• Production Engineering
• Big Data
• Statistical Theories
• Statistical Methods

• Oregon Health & Science University , Portland, USA

  Dongseok Choi

• Pukyong National University , Busan, Korea (Republic of)

  Daeheung Jang

• Stanford University, Stanford, USA

  Tze Leung Lai

• Seoul National University, Gwanak-gu, Seoul, Korea (Republic of)

  Youngjo Lee

• Stanford University , Stanford, USA

  Ying Lu

• University of Michigan–Ann Arbor, Ann Arbor, USA

  Jun Ni

• University of Wisconsin–Madison, Madison, USA

  Peter Qian

• University of Florida, Gainesville, USA

  Peihua Qiu

• University of Chicago , Chicago, USA

  George Tiao

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