The main scope of the paper is performing appropriate kriging interpolation of the diabetes prevalence data coming from the Pavia (Italy) Local Health Care Agency (ASL). The original dataset is analyzed, the Bayesian regularization is evaluated, which is applied by other authors and finally prevalence data are simulated by means of random fields, in order to tune and evaluate kriging interpolation.

Filtering and Mapping Public Health Data with an Innovative Kriging Approach, Accounting for Single Observation Variance / Casella, Vittorio; Manzino, Ambrogio; Bellazzi, Riccardo; Franzini, Marica. - In: PROCEDIA ENVIRONMENTAL SCIENCES. - ISSN 1878-0296. - STAMPA. - 26:(2015), pp. 57-61. ((Intervento presentato al convegno Spatial Statistics: Emerging Patterns tenutosi a Avignon, France nel 9-12 June 2015 [10.1016/j.proenv.2015.05.024].

Filtering and Mapping Public Health Data with an Innovative Kriging Approach, Accounting for Single Observation Variance

CASELLA, VITTORIO;MANZINO, AMBROGIO;
2015

Abstract

The main scope of the paper is performing appropriate kriging interpolation of the diabetes prevalence data coming from the Pavia (Italy) Local Health Care Agency (ASL). The original dataset is analyzed, the Bayesian regularization is evaluated, which is applied by other authors and finally prevalence data are simulated by means of random fields, in order to tune and evaluate kriging interpolation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2625799
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