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Statistical modeling with counts of ...

Ingersoll, Thomas Eugene.

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Statistical modeling with counts of bats.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical modeling with counts of bats./
作者:	Ingersoll, Thomas Eugene.
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
Contained By:	Dissertation Abstracts International72-06B.
標題:	Biology, Biostatistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3448989
ISBN:	9781124553665

Statistical modeling with counts of bats.
Ingersoll, Thomas Eugene.

Statistical modeling with counts of bats. - 115 p.

Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .

Thesis (Ph.D.)--University of California, Berkeley, 2010.

Count data are often the most available indices for bat abundance. Counts of bats are useful for estimating differences in population size, between different habitats, or at different times. But such estimates are not without complications. We used pre-existing bat count data sets, and simulated bat count data to survey a variety of methods for interpreting bat counts. These methods included, evaluation of habitat preferences through AIC model selection of generalized linear models, evaluation of differences in abundance using hierarchical models, and evaluation of spatially replicated time series dynamics using additive mixed-models. All methods proved useful under the special circumstances that accommodated model assumptions. Generalized linear models required the most restrictive assumptions, while hierarchical and additive models allowed many assumptions to be relaxed. We identified several areas where current modeling practices might be improved.

ISBN: 9781124553665Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Statistical modeling with counts of bats.
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500 $a Source: Dissertation Abstracts International, Volume: 72-06, Section: B, page: .
500 $a Adviser: Perry de Valpine.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2010.
520 $a Count data are often the most available indices for bat abundance. Counts of bats are useful for estimating differences in population size, between different habitats, or at different times. But such estimates are not without complications. We used pre-existing bat count data sets, and simulated bat count data to survey a variety of methods for interpreting bat counts. These methods included, evaluation of habitat preferences through AIC model selection of generalized linear models, evaluation of differences in abundance using hierarchical models, and evaluation of spatially replicated time series dynamics using additive mixed-models. All methods proved useful under the special circumstances that accommodated model assumptions. Generalized linear models required the most restrictive assumptions, while hierarchical and additive models allowed many assumptions to be relaxed. We identified several areas where current modeling practices might be improved.
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650 4 $a Biology, Ecology. $3 1017726
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710 2 $a University of California, Berkeley. $b Environmental Science, Policy, & Management. $3 1678657
773 0 $t Dissertation Abstracts International $g 72-06B.
790 1 0 $a de Valpine, Perry, $e advisor
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790 1 0 $a Beissinger, Steven R. $e committee member
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791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3448989