Sangalli, Laura M.; Ramsay, James O.; Ramsay, Timothy O. Spatial spline regression models. (English) Zbl 1411.62134 J. R. Stat. Soc., Ser. B, Stat. Methodol. 75, No. 4, 681-703 (2013). 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. Cited in 36 Documents MSC: 62H11 Directional data; spatial statistics 62G08 Nonparametric regression and quantile regression 62-07 Data analysis (statistics) (MSC2010) Keywords:finite elements; functional data analysis; penalized smoothing; semiparametric model; spatial data analysis PDFBibTeX XMLCite \textit{L. M. Sangalli} et al., J. R. Stat. Soc., Ser. B, Stat. Methodol. 75, No. 4, 681--703 (2013; Zbl 1411.62134) Full Text: DOI