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Spatial spline regression models
Author(s) -
Sangalli Laura M.,
Ramsay James O.,
Ramsay Timothy O.
Publication year - 2013
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/rssb.12009
Subject(s) - spline (mechanical) , covariate , spatial analysis , piecewise , computer science , segmented regression , quadratic equation , regression analysis , regression , algorithm , mathematics , data mining , polynomial regression , statistics , geometry , mathematical analysis , engineering , structural engineering
Summary We describe a model for the analysis of data distributed over irregularly shaped spatial domains with complex boundaries, strong concavities and interior holes. Adopting an approach that is typical of functional data analysis, we propose a spatial spline regression model that is computationally efficient, allows for spatially distributed covariate information and can impose various conditions over the boundaries of the domain. Accurate surface estimation is achieved by the use of piecewise linear and quadratic finite elements.