Package: RSE 1.3

RSE: Number of Newly Discovered Rare Species Estimation

A Bayesian-weighted estimator and two unweighted estimators are developed to estimate the number of newly found rare species in additional ecological samples. Among these methods, the Bayesian-weighted estimator and an unweighted (Chao-derived) estimator are of high accuracy and recommended for practical applications. Technical details of the proposed estimators have been well described in the following paper: Shen TJ, Chen YH (2018) A Bayesian weighted approach to predicting the number of newly discovered rare species. Conservation Biology, In press.

Authors:Youhua Chen,Tsung-Jen Shen

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RSE/json (API)

# Install 'RSE' in R:
install.packages('RSE', repos = c('https://youhuachen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • CanadaMite - Mite incidence in moss patches of 32 locations of western Canada
  • HerpetologicalData - Abundance of herpetofauna in the conserved and human disturbed areas of Mexico

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.03 score 18 scripts 132 downloads 6 mentions 15 exports 0 dependencies

Last updated 6 years agofrom:6a9ab901da. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:boot.abundance.funboot.incidence.funDetAbuDetIncf.to.XPred.abundance.rarePred.Fk.BWPred.Fk.NaivePred.Fk.unweightedPred.incidence.rarePred.Qk.BWPred.Qk.NaivePred.Qk.unweightedSpEst.Chao1.abunX.to.f

Dependencies: