Package: ecocbo 0.12.0

ecocbo: Calculating Optimum Sampling Effort in Community Ecology

A system for calculating the optimal sampling effort, based on the ideas of "Ecological cost-benefit optimization" as developed by A. Underwood (1997, ISBN 0 521 55696 1). Data is obtained from simulated ecological communities with prep_data() which formats and arranges the initial data, and then the optimization follows the following procedure of four functions: (1) scompvar() calculates the variation components necessary for (2) sim_cbo() to calculate the optimal combination of number of sites and samples depending on either an economic budget or on a desired statistical accuracy. Additionally, (3) sim_beta() estimates statistical power and type 2 error by using Permutational Multivariate Analysis of Variance, and (6) plot_power() represents the results of the previous function.

Authors:Edlin Guerra-Castro [aut, cph], Arturo Sanchez-Porras [aut, cre]

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NEWS

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

Peer review:

Bug tracker:https://github.com/arturosp/ecocbo/issues

Datasets:
  • epiDat - Dataset on species count of marine communities
  • simResults - Data set containing the results of applying ecocbo::prep_data().

On CRAN:

4.00 score 7 scripts 195 downloads 12 exports 80 dependencies

Last updated 2 months agofrom:468423a068. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winOKOct 26 2024
R-4.5-linuxOKOct 26 2024
R-4.4-winOKOct 26 2024
R-4.4-macOKOct 26 2024
R-4.3-winOKOct 26 2024
R-4.3-macOKOct 26 2024

Exports:balanced_samplingbalanced_sampling2permanova_onewaypermanova_twowayplot_powerprep_dataprep_data_nestedsymmetricprep_data_singlescompvarsim_betasim_cboSS

Dependencies:abindbackportsbootbroomcarcarDatacliclustercodetoolscolorspacecorrplotcowplotcpp11DerivdoBydoParalleldoSNOWdplyrfansifarverforeachFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobanditeratorslabelinglatticelifecyclelme4lpSolvemagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpermutepillarpkgconfigpolynompurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixsamplingscalessnowSparseMSSPstringistringrsurvivaltibbletidyrtidyselectutf8vctrsveganviridisLitewithr

ecocbo-guide

Rendered fromecocbo-guide.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2024-08-06
Started: 2023-05-04