Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

DOI10.1016/j.stamet.2012.10.002zbMath1486.62294OpenAlexW1968112139WikidataQ60457242 ScholiaQ60457242MaRDI QIDQ1731178

Allan F. O'Connell, Elise F. Zipkin, Brian P. Kinlan, Emily D. Silverman, Jeffery B. Leirness

Publication date: 13 March 2019

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1785&context=usgsstaffpub

zbMATH Keywords

model selectionmarked point processnegative binomialcommon eidersdiscretized lognormalgroup size modelinglong-tailed ducksscoters

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Sampling theory, sample surveys (62D05) Population dynamics (general) (92D25)

Related Items (max. 100)

Likelihood-based tests in zero-inflated power series models ⋮ Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression ⋮ Unnamed Item ⋮ A flexible zero-inflated model to address data dispersion

Uses Software

• R
• VGAM
• plfit

Cites Work

• Unnamed Item
• Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
• A first principles derivation of animal group size distributions
• Power-law versus exponential distributions of animal group sizes
• Markov population processes as models of primate social and population dynamics
• Power-Law Distributions in Empirical Data
• Model Selection and Multimodel Inference
• A Brief History of Generative Models for Power Law and Lognormal Distributions
• Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
• An Introduction to the Theory of Point Processes

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