A new concept of depth for central regions is introduced. The proposed depth notion assesses how well an interval fits a given univariate distribution as its zonoid region of level 1/2, and it is extended to the multivariate setting by means of a projection argument. Since central regions capture information about location, scatter, and dependency among several variables, the new depth evaluated on an empirical zonoid region quantifies the degree of similarity (in terms of the features captured by central regions) of the corresponding sample with respect to some reference distribution. Statistical process control and the joint monitoring of multivariate and interval-valued data in terms of location and scale are proposed by exploiting the above-mentioned depth notion

Statistical process control and the joint monitoring of multivariate through the zonoid region parameter depth / Pandolfo, Giuseppe; Cascos, Ignacio; Sinova, Beatriz. - (2023). (Intervento presentato al convegno CMStatistics 2023).

Statistical process control and the joint monitoring of multivariate through the zonoid region parameter depth

Giuseppe Pandolfo
Primo
;
2023

Abstract

A new concept of depth for central regions is introduced. The proposed depth notion assesses how well an interval fits a given univariate distribution as its zonoid region of level 1/2, and it is extended to the multivariate setting by means of a projection argument. Since central regions capture information about location, scatter, and dependency among several variables, the new depth evaluated on an empirical zonoid region quantifies the degree of similarity (in terms of the features captured by central regions) of the corresponding sample with respect to some reference distribution. Statistical process control and the joint monitoring of multivariate and interval-valued data in terms of location and scale are proposed by exploiting the above-mentioned depth notion
2023
Statistical process control and the joint monitoring of multivariate through the zonoid region parameter depth / Pandolfo, Giuseppe; Cascos, Ignacio; Sinova, Beatriz. - (2023). (Intervento presentato al convegno CMStatistics 2023).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/949782
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