Facultade de Fisioterapia

Jackknife empirical likelihood of error variance in partially linear varying-coefficient errors-in-variables models

Liu, Ai-Ai; Liang, Han-Ying
Abstract:
For the partially linear varying-coefficient model when the parametric covariates are measured with additive errors, the estimator of the error variance is defined based on residuals of the model. At the same time, we construct Jackknife estimator as well as Jackknife empirical likelihood statistic of the error variance. Under both the response variables and their associated covariates form a stationary -mixing sequence, we prove that the proposed estimators and Jackknife empirical likelihood statistic are asymptotic normality and asymptotic distribution, respectively. Numerical simulations are carried out to assess the performance of the proposed method.
Year:
2017
Type of Publication:
Article
Keywords:
Asymptotic normality; Error variance; Jackknife empirical likelihood; Varying-coefficient errors-in-variables model; alpha-Mixing
Journal:
Statistical Papers
Volume:
58
Number:
1
Pages:
95-122
Month:
March
DOI:
10.1007/s00362-015-0689-8
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