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RSE  

Number of Newly Discovered Rare Species Estimation
View on CRAN: Click here


Download and install RSE package within the R console
Install from CRAN:
install.packages("RSE")

Install from Github:
library("remotes")
install_github("cran/RSE")

Install by package version:
library("remotes")
install_version("RSE", "1.3")



Attach the package and use:
library("RSE")
Maintained by
Youhua Chen
[Scholar Profile | Author Map]
First Published: 2018-10-19
Latest Update: 2018-11-20
Description:
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.
How to cite:
Youhua Chen (2018). RSE: Number of Newly Discovered Rare Species Estimation. R package version 1.3, https://cran.r-project.org/web/packages/RSE. Accessed 16 Apr. 2025.
Previous versions and publish date:
1.2 (2018-10-19 17:30)
Other packages that cited RSE R package
View RSE citation profile
Other R packages that RSE depends, imports, suggests or enhances
Complete documentation for RSE
Functions, R codes and Examples using the RSE R package
Some associated functions: CanadaMite . DetAbu . DetInc . HerpetologicalData . Pred.Fk.BW . Pred.Fk.Naive . Pred.Fk.unweighted . Pred.Qk.BW . Pred.Qk.Native . Pred.Qk.unweighted . Pred.abundance.rare . Pred.incidence.rare . RSE-package . SpEst.Chao1.abun . X.to.f . boot.abundance.fun . boot.incidence.fun . f.to.X . 
Some associated R codes: RSE.R .  Full RSE package functions and examples
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