Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

Chiara Ghiringhelli

Datos Biográficos

ID9502017
NOMBREChiara Ghiringhelli
NOMBRESChiara
APELLIDOGhiringhelli
FIRMAGHIRINGHELLI C
AFILIACIONESDepartment of Statistical Science Università Cattolica del Sacro Cuore Roma Italy
VERIFICADONo
TOTAL DE OBRAS2
TOTAL DE CITAS0
OBRAS COMO AUTOR2
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2023
AÑO MÁS RECIENTE DE PUBLICACIÓN2023
ÍNDICE H0
  • Effects of Confidentiality‐Preserving Geo‐Masking on the Estimation of Semivariogram and of the Kriging Variance

    Open Access•Giuseppe Arbia, Chiara Ghiringhelli et al.•ARTICLE•Geographical Analysis•2023

    Geostatistical methods, such as semivariograms and kriging are well‐known spatial tools commonly employed in many disciplines such as health, mining, forestry, meteorology to name only few. They are based essentially on point‐referenced data on a continuous space and on the calculation of distances between them. In many practical instances, however, the exact point location, even if exactly known, is geo‐masked to preserve confidentiality. This t…

  • Recursive Estimation of the Spatial Error Model

    Open Access•Chiara Ghiringhelli, Gianfranco Piras et al.•ARTICLE•Geographical Analysis•2023

    In this paper, we propose a recursive approach to estimate the spatial error model. We compare the suggested methodology with standard estimation procedures and we report a set of Monte Carlo experiments which show that the recursive approach substantially reduces the computational effort affecting the precision of the estimators within reasonable limits. The proposed technique can prove helpful when applied to real‐time streams of geographical d…

Sin obras prominentes en esta página.

  • Effects of Confidentiality‐Preserving Geo‐Masking on the Estimation of Semivariogram and of the Kriging Variance

    Open Access•Giuseppe Arbia, Chiara Ghiringhelli et al.•ARTICLE•Geographical Analysis•2023

    Geostatistical methods, such as semivariograms and kriging are well‐known spatial tools commonly employed in many disciplines such as health, mining, forestry, meteorology to name only few. They are based essentially on point‐referenced data on a continuous space and on the calculation of distances between them. In many practical instances, however, the exact point location, even if exactly known, is geo‐masked to preserve confidentiality. This t…

  • Recursive Estimation of the Spatial Error Model

    Open Access•Chiara Ghiringhelli, Gianfranco Piras et al.•ARTICLE•Geographical Analysis•2023

    In this paper, we propose a recursive approach to estimate the spatial error model. We compare the suggested methodology with standard estimation procedures and we report a set of Monte Carlo experiments which show that the recursive approach substantially reduces the computational effort affecting the precision of the estimators within reasonable limits. The proposed technique can prove helpful when applied to real‐time streams of geographical d…

Computer Science (2 obras) · Data mining (2 obras) · Estimation (2 obras) · Mathematics (2 obras) · Soil Geostatistics and Mapping (2 obras) · Spatial and Panel Data Analysis (2 obras) · Statistics (2 obras) · Algorithm (1 obra) · Artificial Intelligence (1 obra) · Artificial Intelligence (1 obra)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae