Estimation in Capture-Recapture Models When Covariates Are Subject To Measurement Errors

淡江大學機構典藏 > 理學院 > 數學學系暨研究所 > 期刊論文 > Item 987654321/58826

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题名:	Estimation in Capture-Recapture Models When Covariates Are Subject To Measurement Errors
作者:	黃逸輝;黃文瀚
贡献者:	淡江大學數學學系
日期:	2003-11-01
上传时间:	2011-10-01 21:14:13 (UTC+8)
摘要:	Summary. We consider estimation problems in capture-recapture models when the covariates or the auxiliary variables are measured with errors. The naive approach, which ignores measurement errors, is found to be unacceptable in the estimation of both regression parameters and population size: it yields estimators with biases increasing with the magnitude of errors, and flawed confidence intervals. To account for measurement errors, we derive a regression parameter estimator using a regression calibration method. We develop modified estimators of the population size accordingly. A simulation study shows that the resulting estimators are more satisfactory than those from either the naive approach or the simulation extrapolation (SIMEX) method. Data from a bird species Prinia flaviventris in Hong Kong are analyzed with and without the assumption of measurement errors, to demonstrate the effects of errors on estimations.
關聯:	Biometrics 59, pp.1113-1122
DOI:	10.1111/j.0006-341X.2003.00128.x
显示于类别:	[數學學系暨研究所] 期刊論文

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