This paper deals with an analysis of random effects for micro-electronic data. More precisely, by considering the technical challenges related to the use of Electrically Conductive Adhesives (ECAs) such as soldering material in electronics, the sources of variabilities related to different ECA characteristics and working process variables are evaluated. Random effects are involved in a Response Surface Methodology (RSM) setting and the results are compared with a Bayesian approach, where variance components are estimated through a log-posterior expressed as the product of the information matrix and Restricted Maximum Likelihood (REML) estimates of variance components.

Mixed Response Surface models and Bayesian analysis of variance components for Electrically Conductive Adhesives / R. Berni; V.L. Scarano; F. Bertocci; M. Catelani. - In: APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY. - ISSN 1524-1904. - STAMPA. - 29:(2013), pp. 387-398. [10.1002/asmb.1978]

Mixed Response Surface models and Bayesian analysis of variance components for Electrically Conductive Adhesives

BERNI, ROSSELLA;SCARANO, VALERIA LEONARDA;BERTOCCI, FRANCESCO;CATELANI, MARCANTONIO
2013

Abstract

This paper deals with an analysis of random effects for micro-electronic data. More precisely, by considering the technical challenges related to the use of Electrically Conductive Adhesives (ECAs) such as soldering material in electronics, the sources of variabilities related to different ECA characteristics and working process variables are evaluated. Random effects are involved in a Response Surface Methodology (RSM) setting and the results are compared with a Bayesian approach, where variance components are estimated through a log-posterior expressed as the product of the information matrix and Restricted Maximum Likelihood (REML) estimates of variance components.
2013
29
387
398
R. Berni; V.L. Scarano; F. Bertocci; M. Catelani
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/796072
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