Artículos con órdenes de acceso público - Lu LuMás información
Disponibles en algún lugar: 30
General path models for degradation data with multiple characteristics and covariates
L Lu, B Wang, Y Hong, Z Ye
Technometrics 63 (3), 354-369, 2021
Órdenes: US Department of Defense, National Natural Science Foundation of China
A data heterogeneity modeling and quantification approach for field pre-assessment of chloride-induced corrosion in aging infrastructures
S Chen, L Lu, Y Xiang, Q Lu, M Li
Reliability Engineering & System Safety 171, 123-135, 2018
Órdenes: US National Science Foundation, National Natural Science Foundation of China
Effective interdisciplinary collaboration between statisticians and other subject matter experts
CM Anderson-Cook, L Lu, PA Parker
Quality Engineering 31 (1), 164-176, 2019
Órdenes: US Department of Energy
Multiple response optimization for higher dimensions in factors and responses
L Lu, JL Chapman, CM Anderson‐Cook
Quality and Reliability Engineering International 33 (4), 727-744, 2017
Órdenes: US Department of Energy
Multiple objective optimization in reliability demonstration tests
L Lu, M Li, CM Anderson-Cook
Journal of Quality Technology 48 (4), 326-342, 2016
Órdenes: US Department of Energy
Multi-state reliability demonstration tests
S Chen, L Lu, M Li
Quality Engineering 29 (3), 431-445, 2017
Órdenes: US National Science Foundation
How to host an effective data competition: Statistical advice for competition design and analysis
CM Anderson‐Cook, KL Myers, L Lu, ML Fugate, KR Quinlan, N Pawley
Statistical Analysis and Data Mining: The ASA Data Science Journal 12 (4 …, 2019
Órdenes: US Department of Energy
Comparing Kaplan‐Meier curves with the probability of agreement
NT Stevens, L Lu
Statistics in Medicine 39 (30), 4621-4635, 2020
Órdenes: US Department of Defense, Natural Sciences and Engineering Research Council …
Graphics to facilitate informative discussion and team decision making
CM Anderson‐Cook, L Lu
Applied Stochastic Models in Business and Industry 34 (6), 963-980, 2018
Órdenes: US Department of Energy
Improved learning from data competitions through strategic design of training and test data sets
CM Anderson-Cook, L Lu, KL Myers, KR Quinlan, N Pawley
Quality Engineering 31 (4), 564-580, 2019
Órdenes: US Department of Energy
Best Bang for the Buck: Part 1–The Size of Experiments Relative to Design Performance
CM Anderson-Cook, L Lu
Quality Progress 49 (LA-UR-16-26820), 2016
Órdenes: US Department of Energy
Input‐response space‐filling designs
L Lu, CM Anderson‐Cook
Quality and Reliability Engineering International 37 (8), 3529-3551, 2021
Órdenes: US Department of Energy
Best Bang for the Buck: Part 2–Choosing Between Different Sized Designs
CM Anderson-Cook, L Lu
Quality Progress 49 (LA-UR-16-26819), 2016
Órdenes: US Department of Energy
Bayesian probability of agreement for comparing survival or reliability functions with parametric lifetime regression models
NT Stevens, L Lu, CM Anderson-Cook, SE Rigdon
Quality Engineering 32 (3), 312-332, 2020
Órdenes: Natural Sciences and Engineering Research Council of Canada
Practical choices for space‐filling designs
L Lu, CM Anderson‐Cook, M Martin, T Ahmed
Quality and Reliability Engineering International 38 (3), 1165-1188, 2022
Órdenes: US Department of Energy
Choosing a reliability inspection plan for interval censored data
L Lu, CM Anderson-Cook
Quality Engineering 29 (3), 512-535, 2017
Órdenes: US Department of Energy
Prioritization of stockpile maintenance with layered Pareto fronts
SE Burke, CM Anderson-Cook, L Lu, DC Montgomery
Quality Engineering 30 (4), 556-568, 2018
Órdenes: US Department of Energy
Quality quandaries: Understanding aspects influencing different types of multiple response optimization
CM Anderson-Cook, Y Cao, L Lu
Quality Engineering 29 (2), 329-341, 2017
Órdenes: US Department of Energy
Using a baseline with the probability of agreement to compare distribution characteristics
L Lu, CM Anderson-Cook, NT Stevens, L Hagar
Quality Engineering 34 (3), 322-343, 2022
Órdenes: US Department of Defense
Bayesian Sequential design based on dual objectives for accelerated life tests
L Lu, IC Lee, Y Hong
Statistical Quality Technologies: Theory and Practice, 257-275, 2019
Órdenes: US National Science Foundation
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