Displaying similar documents to “Rank Test for Testing Randomness of a Regression Coefficient in a Linear Regression Model.”

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.

Aligned rank tests in measurement error model

Radim Navrátil, A. K. Md. Ehsanes Saleh (2016)

Applications of Mathematics

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Aligned rank tests are introduced in the linear regression model with possible measurement errors. Unknown nuisance parameters are estimated first and then classical rank tests are applied on the residuals. Two situations are discussed: testing about an intercept in the linear regression model considering the slope parameter as nuisance and testing of parallelism of several regression lines, i.e. whether the slope parameters of all lines are equal. Theoretical results are derived and...