Displaying similar documents to “On a robust significance test for the Cox regression model”

Goodness-of-fit tests for parametric regression models based on empirical characteristic functions

Marie Hušková, Simon G. Meintanis (2009)

Kybernetika

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Test procedures are constructed for testing the goodness-of-fit in parametric regression models. The test statistic is in the form of an L2 distance between the empirical characteristic function of the residuals in a parametric regression fit and the corresponding empirical characteristic function of the residuals in a non-parametric regression fit. The asymptotic null distribution as well as the behavior of the test statistic under contiguous alternatives is investigated. Theoretical...

Kolmogorov-Smirnov two-sample test based on regression rank scores

Martin Schindler (2008)

Applications of Mathematics

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We derive the two-sample Kolmogorov-Smirnov type test when a nuisance linear regression is present. The test is based on regression rank scores and provides a natural extension of the classical Kolmogorov-Smirnov test. Its asymptotic distributions under the hypothesis and the local alternatives coincide with those of the classical test.

Sign and Wilcoxon tests for quadratic versus cubic regression.

A. P. Gore, K. S. Madhava Rao (1984)

Trabajos de Estadística e Investigación Operativa

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In this paper sign and Wilcoxon tests for testing the null hypothesis of quadratic regression versus the alternative, cubic regression are proposed. It is shown that in the case of a simple design consisting of multiple Y observations at each of the four levels of x, the proposed tests perform reasonably well as compared to their parametric competitors, while in the case of a general design consisting of a large number of levels of x, the loss in Pitman efficiency is considerable. However...

A comparison of cointegration tests

Petr Mariel (1996)

Applications of Mathematics

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In this paper some of the cointegration tests applied to a single equation are compared. Many of the existent cointegration tests are simply extensions of the unit root tests applied to the residuals of the cointegrating regression and the habitual H 0 is no cointegration. However, some non residual-based tests and some tests of the opposite null hypothesis have recently appeared in literature. Monte Carlo simulations have been used for the power comparison of the nine selected tests (...