(Q57062158)

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Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error

article by Péter Sólymos et al published 4 January 2012 in Environmetrics

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Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error (English)

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Péter Sólymos

1

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Erin M. Bayne

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Erin Bayne

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3

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Subhash Lele

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2

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publication date

4 January 2012

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published in

Environmetrics

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volume

23

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issue

2

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page(s)

197-205

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BREEDING BIRD COMMUNITIES IN BOREAL FOREST OF WESTERN CANADA: CONSEQUENCES OF “UNMIXING” THE MIXEDWOODS

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Modeling abundance using N-mixture models: the importance of considering ecological mechanisms

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Model complexity and information in the data: could it be a house built on sand?

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N-mixture models for estimating population size from spatially replicated counts.

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Estimating species occurrence, abundance, and detection probability using zero-inflated distributions

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Modelling occurrence and abundance of species when detection is imperfect

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IMPROVING PRECISION AND REDUCING BIAS IN BIOLOGICAL SURVEYS: ESTIMATING FALSE-NEGATIVE ERROR RATES

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7 January 2021

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Monitoring of biological diversity in space and time

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10.1002/ENV.1149

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(Q57062158)

Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error

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