TY - GEN
T1 - Parametric test metrics estimation using non-Gaussian copulas
AU - Beznia, Kamel
AU - Bounceur, Ahcène
AU - Mir, Salvador
AU - Euler, Reinhardt
PY - 2011
Y1 - 2011
N2 - The evaluation of parametric test metrics for analog/ RF test techniques requires an accurate multivariate statistical model of output parameters of the device under test, namely performances and test measurements. In this paper, we will use Copulas theory for deriving such a model. A copulas-based model separates the dependencies between these output parameters from their marginal distributions, providing a complete and scale-free description of dependence that is more suitable to be modeled using well known multivariate parametric laws. Previous works have used Gaussian copulas for modeling the dependencies between the output parameters for some types of devices (e.g RF LNA). This paper will illustrate the use of Archimedean copulas for modeling non-Gaussian dependencies. In particular, a Clayton copula will be used to model the dependencies between the output parameters of a case-study test technique for CMOS imagers. Parametric test metrics such as pixel false acceptance and false rejection will be estimated using the derived model.
AB - The evaluation of parametric test metrics for analog/ RF test techniques requires an accurate multivariate statistical model of output parameters of the device under test, namely performances and test measurements. In this paper, we will use Copulas theory for deriving such a model. A copulas-based model separates the dependencies between these output parameters from their marginal distributions, providing a complete and scale-free description of dependence that is more suitable to be modeled using well known multivariate parametric laws. Previous works have used Gaussian copulas for modeling the dependencies between the output parameters for some types of devices (e.g RF LNA). This paper will illustrate the use of Archimedean copulas for modeling non-Gaussian dependencies. In particular, a Clayton copula will be used to model the dependencies between the output parameters of a case-study test technique for CMOS imagers. Parametric test metrics such as pixel false acceptance and false rejection will be estimated using the derived model.
UR - https://www.scopus.com/pages/publications/84857165795
U2 - 10.1109/IMS3TW.2011.19
DO - 10.1109/IMS3TW.2011.19
M3 - Conference contribution
AN - SCOPUS:84857165795
SN - 9780769544793
T3 - Proceedings - 2011 IEEE 17th International Mixed-Signals, Sensors and Systems Test Workshop, IMS3TW 2011
SP - 48
EP - 52
BT - Proceedings - 2011 IEEE 17th International Mixed-Signals, Sensors and Systems Test Workshop, IMS3TW 2011
T2 - 2011 IEEE 17th International Mixed-Signals, Sensors and Systems Test Workshop, IMS3TW 2011
Y2 - 16 May 2011 through 18 May 2011
ER -