Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

A non-parametric test for the bivariate c-sample problem is proposed. The test is an extension of a bivariate two-sample test given by Mardia (1967) and possesses various desirable properties. We ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 35, No. 2 (Jun., 2007), pp. 249-264 (16 pages) The authors propose a goodness-of-fit test for parametric regression models ...

Parametric tests make assumptions that aspects of the data follow some sort of theoretical probability distribution. Non-parametric tests or distribution free methods do not, and are used when the ...

We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.

Nonparametric methods form an important core of statistical techniques and are typically used when data do not meet parametric assumptions. Understanding the foundation of these methods, as well as ...

The foundation of parametric test within semiconductor manufacturing is its usefulness in determining that wafers have been fabricated properly. Foundries use parametric test results to help verify ...

SANTA ROSA, Calif.--(BUSINESS WIRE)--Keysight Technologies, Inc. (NYSE: KEYS), a leading technology company that delivers advanced design and validation solutions to help accelerate innovation to ...