We introduce a new family of Wald-type tests, based on minimum Rényi pseudodistance estimators, for testing general linear hypotheses and the variance of the residuals in the multiple regression model. The classical Wald test, based on the maximum likelihood estimator, can be seen as a particular case inside our family. Theoretical results, supported by an extensive simulation study, point out how some tests included in this family have a better behaviour, in the sense of robustness, than the Wald test. Finally, we provide a data-driven procedure for the choice of the optimal test given any data set.Depto. de Economía Financiera y Actuarial y EstadísticaDepto. de Estadística e Investigación OperativaFac. de Ciencias Económicas y Empresarial...
Under the maximum likelihood framework, three asymptotic overall tests have been well developed in g...
Zhang (2019) presented a general estimation approach based on the Gaussian distribution for general ...
Since statistical models are simplifications of reality, it is important in estimation theory to stu...
We introduce a new family of Wald-type tests, based on minimum Rényi pseudodistance estimators, for ...
Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value cor...
In real life we often deal with independent but not identically distributed observations (i.n.i.d.o)...
In real life we often deal with independent but not identically distributed observations (i.n.i.d.o)...
The Rao’s score, Wald and likelihood ratio tests are the most common procedures for testing hypothes...
In testing of hypothesis, the robustness of the tests is an important concern. Generally, the maximu...
Minimum Renyi’s pseudodistance estimators (MRPEs) enjoy good robustness properties without a signifi...
Abstract: We consider R-estimation in the linear model, with an eye to obtaining those estimators, a...
We consider a robust version of the classical Wald test statistics for testing simple and composite ...
The Wald, likelihood ratio and Lagrange multiplier test statistics are commonly used to test linear ...
The Wald, likelihood ratio and Lagrange multiplier test statistics are commonly used to test linear ...
We consider a robust version of the classical Wald test statistics for testing simple and composite ...
Under the maximum likelihood framework, three asymptotic overall tests have been well developed in g...
Zhang (2019) presented a general estimation approach based on the Gaussian distribution for general ...
Since statistical models are simplifications of reality, it is important in estimation theory to stu...
We introduce a new family of Wald-type tests, based on minimum Rényi pseudodistance estimators, for ...
Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value cor...
In real life we often deal with independent but not identically distributed observations (i.n.i.d.o)...
In real life we often deal with independent but not identically distributed observations (i.n.i.d.o)...
The Rao’s score, Wald and likelihood ratio tests are the most common procedures for testing hypothes...
In testing of hypothesis, the robustness of the tests is an important concern. Generally, the maximu...
Minimum Renyi’s pseudodistance estimators (MRPEs) enjoy good robustness properties without a signifi...
Abstract: We consider R-estimation in the linear model, with an eye to obtaining those estimators, a...
We consider a robust version of the classical Wald test statistics for testing simple and composite ...
The Wald, likelihood ratio and Lagrange multiplier test statistics are commonly used to test linear ...
The Wald, likelihood ratio and Lagrange multiplier test statistics are commonly used to test linear ...
We consider a robust version of the classical Wald test statistics for testing simple and composite ...
Under the maximum likelihood framework, three asymptotic overall tests have been well developed in g...
Zhang (2019) presented a general estimation approach based on the Gaussian distribution for general ...
Since statistical models are simplifications of reality, it is important in estimation theory to stu...