Employing Distances in Design-based Spatial Estimation

Vagheggini, Alessandro (2013) Employing Distances in Design-based Spatial Estimation, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Metodologia statistica per la ricerca scientifica, 25 Ciclo. DOI 10.6092/unibo/amsdottorato/5172.
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In the last couple of decades we assisted to a reappraisal of spatial design-based techniques. Usually the spatial information regarding the spatial location of the individuals of a population has been used to develop efficient sampling designs. This thesis aims at offering a new technique for both inference on individual values and global population values able to employ the spatial information available before sampling at estimation level by rewriting a deterministic interpolator under a design-based framework. The achieved point estimator of the individual values is treated both in the case of finite spatial populations and continuous spatial domains, while the theory on the estimator of the population global value covers the finite population case only. A fairly broad simulation study compares the results of the point estimator with the simple random sampling without replacement estimator in predictive form and the kriging, which is the benchmark technique for inference on spatial data. The Monte Carlo experiment is carried out on populations generated according to different superpopulation methods in order to manage different aspects of the spatial structure. The simulation outcomes point out that the proposed point estimator has almost the same behaviour as the kriging predictor regardless of the parameters adopted for generating the populations, especially for low sampling fractions. Moreover, the use of the spatial information improves substantially design-based spatial inference on individual values.

Tipologia del documento
Tesi di dottorato
Vagheggini, Alessandro
Dottorato di ricerca
Scuola di dottorato
Scienze economiche e statistiche
Settore disciplinare
Settore concorsuale
Parole chiave
Spatial estimation; Design-based inference; Spatial sampling; Ratio estimator
Data di discussione
18 Febbraio 2013

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