logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Adaptive Probability-Based Latin Hypercube Designs

delete2011-03-01
delete11
PRE
AI
Y
Ying Hung *
DOI：10.1198/jasa.2011.tm10337delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Adaptive sampling is an effective method developed mainly for regular regions. However, experimental regions in irregular shapes are commonly observed in practice. Motivated by a data center thermal management study, a new class of adaptive designs is proposed to accommodate a specific type of irregular region. Because the adaptive procedure introduces biases into conventional estimators, several design-unbiased estimators are given for estimating the population mean. Efficient and easy-to-compute unbiased estimators are also introduced. The proposed method is applied to obtain an adaptive sensor placement plan to monitor and study the thermal distribution in a data center. All of the supplemental materials used in this work are available online.
Keywords:
Adaptive cluster sampling
Computer experiment
Latin hypercube design
Rao-Blackwell method
Sequential design
Space-filling design
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

J
Journal of the American Statistical Association
IF:
3
Papers:
5.1K
Citations:
4.8W

Organization

No organization information available