A simple two-step method for spatio-temporal design-based balanced sampling
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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https://doi.org/10.1007/s00477-017-1409-9 |
Metadatos
Título
A simple two-step method for spatio-temporal design-based balanced samplingFecha de publicación
2017Editor
Springer Berlin HeidelbergISSN
1436-3240; 1436-3259Cita bibliográfica
KHAVARZADEH, Ramin; MOHAMMADZADEH, Mohsen; MATEU, Jorge. A simple two-step method for spatio-temporal design-based balanced sampling. Stochastic Environmental Research and Risk Assessment, 2018, vol. 32, núm. 2: p. 457-468Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s00477-017-1409-9Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
We introduce a two-step method to perform spatio-temporal balanced sampling in a design-based approach. For populations with spatio-temporal trends and with anisotropic effects in the variable of interest, the prediction ... [+]
We introduce a two-step method to perform spatio-temporal balanced sampling in a design-based approach. For populations with spatio-temporal trends and with anisotropic effects in the variable of interest, the prediction can be further improved by selecting samples that are well spread over the entire population in space and time. We control the spread of the sample over the population by using the volume of the corresponding three-dimensional Voronoi tessellation. Indeed, spatio-temporal design-based balanced sampling is even more efficient under the presence of a trend and anisotropic effects. We present an intensive simulation study comparing our method to other available methods for spatio-temporal sampling. Finally, we analyze real data by sampling from a population of temperature stations over six European countries. [-]
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Stochastic Environmental Research and Risk Assessment, 2018, vol. 32, núm. 2: p. 457-468Derechos de acceso
© Springer-Verlag Berlin Heidelberg 2017
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