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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/58826


    Title: Estimation in Capture-Recapture Models When Covariates Are Subject To Measurement Errors
    Authors: 黃逸輝;黃文瀚
    Contributors: 淡江大學數學學系
    Date: 2003-11-01
    Issue Date: 2011-10-01 21:14:13 (UTC+8)
    Abstract: 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.
    Relation: Biometrics 59, pp.1113-1122
    DOI: 10.1111/j.0006-341X.2003.00128.x
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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