Observing complete functions as a result of random experiments is nowadays possible by the development of real-time measurement instruments and data storage resources. Functional data analysis deals with the statistical description and modeling of samples of random functions. Functional versions for a wide range of statistical tools have been recently developed. Here we are interested in the case of functional data presenting spatial dependence, and the problem is handled from the geostatistical and point process contexts. Functional kriging prediction and clustering are developed. Additionally, we propose functional global and local marked second-order characteristics.
(2011). Spatially correlated functional data [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/25230
Spatially correlated functional data
2011-01-01
Abstract
Observing complete functions as a result of random experiments is nowadays possible by the development of real-time measurement instruments and data storage resources. Functional data analysis deals with the statistical description and modeling of samples of random functions. Functional versions for a wide range of statistical tools have been recently developed. Here we are interested in the case of functional data presenting spatial dependence, and the problem is handled from the geostatistical and point process contexts. Functional kriging prediction and clustering are developed. Additionally, we propose functional global and local marked second-order characteristics.File | Dimensione del file | Formato | |
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