geofd
geofd: an R package for function-valued geostatistical prediction. 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.
Keywords for this software
References in zbMATH (referenced in 7 articles )
Showing results 1 to 7 of 7.
Sorted by year (- Martínez-Hernández, Israel; Genton, Marc G.: Recent developments in complex and spatially correlated functional data (2020)
- Menafoglio, Alessandra; Secchi, Piercesare: Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics (2017)
- Delicado, Pedro: Discussion of “Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan” by Piercesare Secchi, Simone Vantini and Valeria Vitelli (2015)
- Romano, Elvira; Mateu, Jorge; Giraldo, Ramon: On the performance of two clustering methods for spatial functional data (2015)
- Menafoglio, Alessandra; Secchi, Piercesare; Dalla Rosa, Matilde: A universal kriging predictor for spatially dependent functional data of a Hilbert space (2013)
- Giraldo, Ramón; Mateu, Jorge; Delicado, Pedro: geofd: an R package for function-valued geostatistical prediction (2012)
- Manuel Febrero-Bande; Manuel de la Fuente: Statistical Computing in Functional Data Analysis: The R Package fda.usc (2012) not zbMATH