# Estimation of the size of a closed population

Applicationes Mathematicae (2010)

- Volume: 37, Issue: 2, page 237-245
- ISSN: 1233-7234

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topS. Sengupta. "Estimation of the size of a closed population." Applicationes Mathematicae 37.2 (2010): 237-245. <http://eudml.org/doc/279907>.

@article{S2010,

abstract = {The problem considered is that of estimation of the size (N) of a closed population under three sampling schemes admitting unbiased estimation of N. It is proved that for each of these schemes, the uniformly minimum variance unbiased estimator (UMVUE) of N is inadmissible under square error loss function. For the first scheme, the UMVUE is also the maximum likelihood estimator (MLE) of N. For the second scheme and a special case of the third, it is shown respectively that an MLE and an estimator which differs from an MLE by at most one have uniformly smaller mean square errors than the respective UMVUE's.},

author = {S. Sengupta},

journal = {Applicationes Mathematicae},

keywords = {capture-recapture sampling},

language = {eng},

number = {2},

pages = {237-245},

title = {Estimation of the size of a closed population},

url = {http://eudml.org/doc/279907},

volume = {37},

year = {2010},

}

TY - JOUR

AU - S. Sengupta

TI - Estimation of the size of a closed population

JO - Applicationes Mathematicae

PY - 2010

VL - 37

IS - 2

SP - 237

EP - 245

AB - The problem considered is that of estimation of the size (N) of a closed population under three sampling schemes admitting unbiased estimation of N. It is proved that for each of these schemes, the uniformly minimum variance unbiased estimator (UMVUE) of N is inadmissible under square error loss function. For the first scheme, the UMVUE is also the maximum likelihood estimator (MLE) of N. For the second scheme and a special case of the third, it is shown respectively that an MLE and an estimator which differs from an MLE by at most one have uniformly smaller mean square errors than the respective UMVUE's.

LA - eng

KW - capture-recapture sampling

UR - http://eudml.org/doc/279907

ER -

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