The majority of actions designed to improve processes and quality include the assessment of the capability of a measurement system. The statistical model relating the measured value to the true, but not observable, value of a product characteristic is usually Gaussian and additive. In this paper we propose to extend the said model to a more general formulation by introducing the structure of the two-component error model. An approximated method for evaluating the misclassification rates under the two-component error model is proposed and assessed.
A robust approach for assessing misclassification rates under the two-component measurement error model / Daniela Cocchi; Michele Scagliarini. - In: APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY. - ISSN 1524-1904. - STAMPA. - 26:(2010), pp. 389-400. [10.1002/asmb.793]
A robust approach for assessing misclassification rates under the two-component measurement error model
COCCHI, DANIELA;SCAGLIARINI, MICHELE
2010
Abstract
The majority of actions designed to improve processes and quality include the assessment of the capability of a measurement system. The statistical model relating the measured value to the true, but not observable, value of a product characteristic is usually Gaussian and additive. In this paper we propose to extend the said model to a more general formulation by introducing the structure of the two-component error model. An approximated method for evaluating the misclassification rates under the two-component error model is proposed and assessed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
