Quality Quandaries: Predicting a Population of Curves

Fugate, Michael Lynn; Hamada, Michael Scott; Weaver, Brian Phillip

doi:10.1080/08982112.2017.1417601

Title: Quality Quandaries: Predicting a Population of Curves

Journal Article · Tue Dec 19 00:00:00 EST 2017 · Quality Engineering

DOI:https://doi.org/10.1080/08982112.2017.1417601· OSTI ID:1416317

^[1]; Hamada, Michael Scott ^[1];

^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

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.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1416317

Report Number(s):: LA-UR-17-30878; TRN: US1800919

Journal Information:: Quality Engineering, Vol. 30, Issue 2; ISSN 0898-2112

Publisher:: American Society for Quality ControlCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 1 work

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References (7)

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