A Model-Based Approach for Making Ecological Inference from Distance Sampling Data
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Publication:3564589
DOI10.1111/j.1541-0420.2009.01265.xzbMath1187.62191OpenAlexW2057030083WikidataQ33449800 ScholiaQ33449800MaRDI QIDQ3564589
Devin S. Johnson, Jeffrey L. Laake, Jay M. Ver Hoef
Publication date: 26 May 2010
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1186&context=usdeptcommercepub
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Related Items (10)
From distance sampling to spatial capture-recapture ⋮ Improving the usability of spatial point process methodology: an interdisciplinary dialogue between statistics and ecology ⋮ Variance Estimation for Systematic Designs in Spatial Surveys ⋮ Estimating abundance from counts in large data sets of irregularly spaced plots using spatial basis functions ⋮ Estimating survival in continuous space from mark-dead-recovery data -- towards a continuous version of the multinomial dead recovery model ⋮ Spatially explicit models for inference about density in unmarked or partially marked populations ⋮ Bayesian methods for hierarchical distance sampling models ⋮ Model-based Prediction In Ecological Surveys Including Those with Incomplete Detection ⋮ Model-based distance sampling ⋮ Variance propagation for density surface models
Uses Software
Cites Work
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