1Universidad Nacional de Colombia, Sciences Faculty, Department of Statistics, Bogotá, Colombia. Associate professor. Email: rgiraldoh@unal.edu.co
2Universitat Jaume I, Department of Mathematics, Castellón, Spain. Professor. Email: mateu@mat.uji.es
3Universitat Politècnica de Catalunya, Department of Statistics and Operations Research, Barcelona, Spain. Associate professor. Email: pedro.delicado@upc.edu
Spatially correlated curves are present in a wide range of applied disciplines. In this paper we describe the R package geofd which implements ordinary kriging prediction for this type of data. Initially the curves are pre-processed by fitting a Fourier or B-splines basis functions. After that the spatial dependence among curves is estimated by means of the trace-variogram function. Finally the parameters for performing prediction by ordinary kriging at unsampled locations are by estimated solving a linear system based estimated trace-variogram. We illustrate the software analyzing real and simulated data.
Key words: Functional data, Smoothing, Spatial data, Variogram.
Curvas espacialmente correlacionadas están presentes en un amplio rango de disciplinas aplicadas. En este trabajo se describe el paquete R geofd que implementa predicción por kriging ordinario para este tipo de datos. Inicialmente las curvas son suavizadas usando bases de funciones de Fourier o B-splines. Posteriormente la dependencia espacial entre las curvas es estimada por la función traza-variograma. Finalmente los parámetros del predictor kriging ordinario son estimados resolviendo un sistema de ecuaciones basado en la estimación de la función traza-variograma. Se ilustra el paquete analizando datos reales y simulados.
Palabras clave: datos funcionales, datos espaciales, suavizado, variograma.
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Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:
@ARTICLE{RCEv35n3a04,
AUTHOR = {Giraldo, Ramón and Mateu, Jorge and Delicado, Pedro},
TITLE = {{geofd: An R Package for Function-Valued Geostatistical Prediction}},
JOURNAL = {Revista Colombiana de Estadística},
YEAR = {2012},
volume = {35},
number = {3},
pages = {383-405}
}