Robust tests for linear models are derived via Wald-type tests that are based on asymptotically linear estimators. For a robustness criterion, the maximum asymptotic bias of the level of the test for ...

SAS/INSIGHT fit analysis provides the traditional parametric regression analysis assuming that the regression function is linear in the unknown parameters. The relationship is expressed as an equation ...

A variety of linear models are available to represent common active electronic devices such as transistors and vacuum tubes. Devices operating under large-signal conditions often require nonlinear ...

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...

As related to the environment pollution from nuclear accident. In my opinion even if LNT was untrue and there existed some threshold for carcinogenic effect of ionizing radiation, the radiation would ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...