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- W3149582010 abstract "Censored regression (Tobit) models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters. In this paper, we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic. It is shown that, under both the null and local alternative hypotheses, conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic. Therefore, the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters. At the same time, we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model. Simulation studies illustrate that the per-formance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis." @default.
- W3149582010 created "2021-04-13" @default.
- W3149582010 creator A5071358702 @default.
- W3149582010 date "2009-01-01" @default.
- W3149582010 modified "2023-09-23" @default.
- W3149582010 title "Approximation by randomly weighting method in censored regression model" @default.
- W3149582010 hasPublicationYear "2009" @default.
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