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In this paper, linear errors-in-response models are considered in the presence of validation data on the responses. A semiparametric dimension reduction technique is employed to define an estimator of Ø with asymptotic normality, the estimated empirical loglikelihoods and the adjusted empirical...
Persistent link: https://www.econbiz.de/10010310551
In this paper, linear errors-in-response models are considered in the presence of validation data on the responses. A semiparametric dimension reduction technique is employed to define an estimator of Ø with asymptotic normality, the estimated empirical loglikelihoods and the adjusted empirical...
Persistent link: https://www.econbiz.de/10010983779
Consider the partial linear models of the formY=X[tau][beta]+g(T)+e, where thep-variate explanatoryXis erroneously measured, and bothTand the responseYare measured exactly. LetXbe the surrogate variable forXwith measurement error. Let the primary data set be that containing independent...
Persistent link: https://www.econbiz.de/10005093833
Consider the linear models of the form Y=X[tau][beta]+[var epsilon] with the response Y censored randomly on the right and X measured erroneously. Without specifying any error models, in this paper, a semiparametric method is applied to the estimation of the parametric vector [beta] with the...
Persistent link: https://www.econbiz.de/10005199570