Imbedding linear regressions in models for factor crossing

Carla Santos; Célia Nunes; Cristina Dias; Maria Varadinov; João T. Mexia

doi:10.1063/1.4968734

Imbedding linear regressions in models for factor crossing

Carla Santos, Célia Nunes, Cristina Dias, Maria Varadinov, João T. Mexia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Given u factors with J₁, ⋯, J_u levels we are led to test their effects and interactions. For this we consider an orthogonal partition of Rⁿ, with n=πl=1uJl, in subspaces associated with the sets of factors. The space corresponding to the set C will have density g(C)=πlϵC(Jl-1) so that g({1, ⋯, u}) will be much larger than the other number of degrees of freedom when J_l > 2, l = 1, ⋯, u This fact may be used to enrich these models imbedding in them linear regressions.

Original language	English
Title of host publication	International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016
Publisher	AIP - American Institute of Physics
Volume	1790
ISBN (Electronic)	9780735414549
DOIs	https://doi.org/10.1063/1.4968734
Publication status	Published - 6 Dec 2016
Event	International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016 - Athens, Greece Duration: 17 Mar 2016 → 20 Mar 2016

Conference

Conference	International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016
Country/Territory	Greece
City	Athens
Period	17/03/16 → 20/03/16

Keywords

Crossing
Effects and Interactions
Orthogonal partition

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title = "Imbedding linear regressions in models for factor crossing",

abstract = "Given u factors with J1, ⋯, Ju levels we are led to test their effects and interactions. For this we consider an orthogonal partition of Rn, with n=πl=1uJl, in subspaces associated with the sets of factors. The space corresponding to the set C will have density g(C)=πlϵC(Jl-1) so that g({1, ⋯, u}) will be much larger than the other number of degrees of freedom when Jl > 2, l = 1, ⋯, u This fact may be used to enrich these models imbedding in them linear regressions.",

keywords = "Crossing, Effects and Interactions, Orthogonal partition",

author = "Carla Santos and C{\'e}lia Nunes and Cristina Dias and Maria Varadinov and Mexia, {Jo{\~a}o T.}",

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day = "6",

doi = "10.1063/1.4968734",

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Santos, C, Nunes, C, Dias, C, Varadinov, M & Mexia, JT 2016, Imbedding linear regressions in models for factor crossing. in International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016. vol. 1790, 140005, AIP - American Institute of Physics, International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016, Athens, Greece, 17/03/16. https://doi.org/10.1063/1.4968734

Imbedding linear regressions in models for factor crossing. / Santos, Carla; Nunes, Célia; Dias, Cristina et al.
International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016. Vol. 1790 AIP - American Institute of Physics, 2016. 140005.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Imbedding linear regressions in models for factor crossing

AU - Santos, Carla

AU - Nunes, Célia

AU - Dias, Cristina

AU - Varadinov, Maria

AU - Mexia, João T.

N1 - Sem PDF conforme despacho.

PY - 2016/12/6

Y1 - 2016/12/6

N2 - Given u factors with J1, ⋯, Ju levels we are led to test their effects and interactions. For this we consider an orthogonal partition of Rn, with n=πl=1uJl, in subspaces associated with the sets of factors. The space corresponding to the set C will have density g(C)=πlϵC(Jl-1) so that g({1, ⋯, u}) will be much larger than the other number of degrees of freedom when Jl > 2, l = 1, ⋯, u This fact may be used to enrich these models imbedding in them linear regressions.

AB - Given u factors with J1, ⋯, Ju levels we are led to test their effects and interactions. For this we consider an orthogonal partition of Rn, with n=πl=1uJl, in subspaces associated with the sets of factors. The space corresponding to the set C will have density g(C)=πlϵC(Jl-1) so that g({1, ⋯, u}) will be much larger than the other number of degrees of freedom when Jl > 2, l = 1, ⋯, u This fact may be used to enrich these models imbedding in them linear regressions.

KW - Crossing

KW - Effects and Interactions

KW - Orthogonal partition

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U2 - 10.1063/1.4968734

DO - 10.1063/1.4968734

M3 - Conference contribution

AN - SCOPUS:85008711885

VL - 1790

BT - International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016

PB - AIP - American Institute of Physics

T2 - International Conference of Computational Methods in Sciences and Engineering 2016, ICCMSE 2016

Y2 - 17 March 2016 through 20 March 2016

ER -

Imbedding linear regressions in models for factor crossing

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Keywords

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