Rank tests for testing randomness of a regression coefficient in a linear regression model

DOI10.1007/BF02613990zbMath0743.62035MaRDI QIDQ1185340

M. B. Rajarshi, T. V. Ramanathan

Publication date: 28 June 1992

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/176400

zbMATH Keywords

asymptotic normalityrank testsempirical processcontiguous alternativesPitman efficiencyasymptotic relative efficienciesrandom coefficient regression modelstesting non-stochasticity

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Related Items (6)

Rank tests for testing the randomness of autoregressive coefficients ⋮ Efficient pseudo-Gaussian and rank-based detection of random regression coefficients ⋮ Optimal pseudo-Gaussian and rank-based random coefficient detection in multiple regression ⋮ Unnamed Item ⋮ Rank Test for Testing Randomness of the Technology Parameters in a Stochastic Frontier Regression Model ⋮ Test for randomness of the technology parameter in a stochastic frontier regression model

Cites Work

• A Simple Test for Heteroscedasticity and Random Coefficient Variation
• Using residuals robustly I: Tests for heteroscedasticity, nonlinearity
• Empirical and rank processes of observations and residuals
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