unmarked

R package unmarked: Models for Data from Unmarked Animals. Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates.

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References in zbMATH (referenced in 10 articles , 1 standard article )

Showing results 1 to 10 of 10.
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  1. Jeffrey W. Doser, Andrew O. Finley, Marc Kery, Elise F. Zipkin: spOccupancy: An R package for single species, multispecies, and integrated spatial occupancy models (2021) arXiv
  2. Karavarsamis, Natalie; Huggins, Richard M.: Two-stage approaches to the analysis of occupancy data i: the homogeneous case (analysis of occupancy data) (2020)
  3. Timothy D. Meehan, Nicole L. Michel, Håvard Rue: Estimating Animal Abundance with N-Mixture Models Using the R-INLA Package for R (2020) not zbMATH
  4. David Miller and Eric Rexstad and Len Thomas and Laura Marshall and Jeffrey Laake: Distance Sampling in R (2019) not zbMATH
  5. Karavarsamis, Natalie: Estimating occupancy and fitting models with the two-stage approach (2019)
  6. Karavarsamis, N.; Huggins, R. M.: Two-stage approaches to the analysis of occupancy data. II: The heterogeneous model and conditional likelihood (2019)
  7. Haines, Linda M.: A note on the Royle-Nichols model for repeated detection-nondetection data (2016)
  8. Dennis, Emily B.; Morgan, Byron J. T.; Ridout, Martin S.: Computational aspects of (N)-mixture models (2015)
  9. McCrea, Rachel S.; Morgan, Byron J. T.: Analysis of capture-recapture data (2015)
  10. Ian Fiske; Richard Chandler: unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance (2011) not zbMATH