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Multivariate Gaussian subspatial regression applied to predict the effect of phosphate crystallization aging on the color in silicious conglomerates
Author(s) -
VicentePalacios Victor,
Iñigo Adolo Carlos,
GarcíaTalegón Jacinta
Publication year - 2017
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.22142
Subject(s) - multivariate statistics , crystallization , conglomerate , phosphate , linear regression , mathematics , regression , gaussian , regression analysis , chromatic scale , mineralogy , materials science , econometrics , thermodynamics , biological system , chemistry , statistics , geology , physics , combinatorics , geochemistry , organic chemistry , computational chemistry , biology , sedimentary rock
A new methodology has been applied to the experimental data obtained about a white siliceous conglomerate from Zamora (Spain), which was subjected to 25 cycles of 2 types of aging [freezing/thawing with cooling/heating (T1) and freezing/thawing with cooling/heating + phosphate crystallization (T2)]. Our model (multivariate Gaussian subspatial regression) allows the behavior and prediction of the chromatic coordinates (L*,a*,b*), including more than 25 cycles, to be analyzed. This model is much more flexible than classical models as it allows multiple variable combinations to be predicted in a dynamic way. The final result showed that the conglomerate experiences darkening, yellowing, and reddening, as the number of cycles increase and that the darkening is much less pronounced in T2 due to phosphate crystallization.