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Title: Quality Quandaries: Predicting a Population of Curves

We present a random effects spline regression model based on splines that provides an integrated approach for analyzing functional data, i.e., curves, when the shape of the curves is not parametrically specified. An analysis using this model is presented that makes inferences about a population of curves as well as features of the curves.
Authors:
ORCiD logo [1] ;  [1] ; ORCiD logo [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Report Number(s):
LA-UR-17-30878
Journal ID: ISSN 0898-2112; TRN: US1800919
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Quality Engineering
Additional Journal Information:
Journal Volume: 30; Journal Issue: 2; Journal ID: ISSN 0898-2112
Publisher:
American Society for Quality Control
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 42 ENGINEERING
OSTI Identifier:
1416317

Fugate, Michael Lynn, Hamada, Michael Scott, and Weaver, Brian Phillip. Quality Quandaries: Predicting a Population of Curves. United States: N. p., Web. doi:10.1080/08982112.2017.1417601.
Fugate, Michael Lynn, Hamada, Michael Scott, & Weaver, Brian Phillip. Quality Quandaries: Predicting a Population of Curves. United States. doi:10.1080/08982112.2017.1417601.
Fugate, Michael Lynn, Hamada, Michael Scott, and Weaver, Brian Phillip. 2017. "Quality Quandaries: Predicting a Population of Curves". United States. doi:10.1080/08982112.2017.1417601.
@article{osti_1416317,
title = {Quality Quandaries: Predicting a Population of Curves},
author = {Fugate, Michael Lynn and Hamada, Michael Scott and Weaver, Brian Phillip},
abstractNote = {We present a random effects spline regression model based on splines that provides an integrated approach for analyzing functional data, i.e., curves, when the shape of the curves is not parametrically specified. An analysis using this model is presented that makes inferences about a population of curves as well as features of the curves.},
doi = {10.1080/08982112.2017.1417601},
journal = {Quality Engineering},
number = 2,
volume = 30,
place = {United States},
year = {2017},
month = {12}
}