A goodness of fit test in Markov models with dependence of covariates.
M. Barrantes, M. González, M. Molina (1995)
Extracta Mathematicae
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Displaying similar documents to “Robust estimation in a linear regression model”
A goodness of fit test in Markov models with dependence of covariates.
Regression quantiles and trimmed least squares estimator under a general design
Jana Jurečková (1984)
Kybernetika
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Combining forecasts using the least trimmed squares
Jan Ámos Víšek (2001)
Kybernetika
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Employing recently derived asymptotic representation of the least trimmed squares estimator, the combinations of the forecasts with constraints are studied. Under assumption of unbiasedness of individual forecasts it is shown that the combination without intercept and with constraint imposed on the estimate of regression coefficients that they sum to one, is better than others. A numerical example is included to support theoretical conclusions.
Some invariant test procedures for detection of structural changes
Marie Hušková (2000)
Kybernetika
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Regression and scale invariant -test procedures are developed for detection of structural changes in linear regression model. Their limit properties are studied under the null hypothesis.
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...