Effect Of Noise In The Estimation Of Magnitudes With Spatial Dependence: A Spatial Statistics Technique Based On Kriging

Kriging is a family of linear methods for the estimation of physical quantities with spatial dependence which are optimal in the squared minima sense. To perform the interpolation, kriging considers, in addition to the value and location of the observations, the spatial correlation of the quantity b...

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Detalles Bibliográficos
Autores: Sánchez Brea, Luis Miguel, Bernabeu Martínez, Eusebio
Tipo de recurso: capítulo de libro
Fecha de publicación:2005
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/53382
Acceso en línea:https://hdl.handle.net/20.500.14352/53382
Access Level:acceso abierto
Palabra clave:535
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Óptica (Física)
2209.19 Óptica Física
Descripción
Sumario:Kriging is a family of linear methods for the estimation of physical quantities with spatial dependence which are optimal in the squared minima sense. To perform the interpolation, kriging considers, in addition to the value and location of the observations, the spatial correlation of the quantity by means of variogram, the random fluctuations of the measured magnitude and the resolution of the measuring devices. The traditional way kriging equations are solved involves the resolution of inverse of great matrices, so that it is normally quite time consuming. Comparing the uncertainty obtained with kriging (for magnitudes with spatial dependence) with standard techniques for uncertainty estimation, we have seen that for the case of regular sampling, the uncertainty estimation can be computed as a convolution.