Abstract
We study capture-recapture models in a closed population when multiple error-prone measurements of a covariate are available. Due to the identity between the number of captures and the number of measurements, no suitable complete and sufficient statistic exists, and the existing method no longer applies. The familiar strategy of generalized method of moments fails to resolve this issue satisfactorily, and complexity lies in the loss of the surrogacy assumption commonly assumed in measurement error problems. Our approach to this problem through a semiparametric treatment overcomes these difficulties. The superior performance of the new method is demonstrated through numerical experiments in simulated and data examples.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1529-1546 |
| Number of pages | 18 |
| Journal | Statistica Sinica |
| Volume | 24 |
| Issue number | 4 |
| DOIs | |
| State | Published - Oct 1 2014 |
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All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
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Effective use of multiple error-prone covariate measurements in capture-recapture models. / Xu, Kun; Ma, Yanyuan.
In: Statistica Sinica, Vol. 24, No. 4, 01.10.2014, p. 1529-1546.Research output: Contribution to journal › Article
TY - JOUR
T1 - Effective use of multiple error-prone covariate measurements in capture-recapture models
AU - Xu, Kun
AU - Ma, Yanyuan
PY - 2014/10/1
Y1 - 2014/10/1
N2 - We study capture-recapture models in a closed population when multiple error-prone measurements of a covariate are available. Due to the identity between the number of captures and the number of measurements, no suitable complete and sufficient statistic exists, and the existing method no longer applies. The familiar strategy of generalized method of moments fails to resolve this issue satisfactorily, and complexity lies in the loss of the surrogacy assumption commonly assumed in measurement error problems. Our approach to this problem through a semiparametric treatment overcomes these difficulties. The superior performance of the new method is demonstrated through numerical experiments in simulated and data examples.
AB - We study capture-recapture models in a closed population when multiple error-prone measurements of a covariate are available. Due to the identity between the number of captures and the number of measurements, no suitable complete and sufficient statistic exists, and the existing method no longer applies. The familiar strategy of generalized method of moments fails to resolve this issue satisfactorily, and complexity lies in the loss of the surrogacy assumption commonly assumed in measurement error problems. Our approach to this problem through a semiparametric treatment overcomes these difficulties. The superior performance of the new method is demonstrated through numerical experiments in simulated and data examples.
UR - http://www.scopus.com/inward/record.url?scp=84946564841&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946564841&partnerID=8YFLogxK
U2 - 10.5705/ss.2012.307
DO - 10.5705/ss.2012.307
M3 - Article
AN - SCOPUS:84946564841
VL - 24
SP - 1529
EP - 1546
JO - Statistica Sinica
JF - Statistica Sinica
SN - 1017-0405
IS - 4
ER -