Package: cxr 1.1.1
cxr: A Toolbox for Modelling Species Coexistence in R
Recent developments in modern coexistence theory have advanced our understanding on how species are able to persist and co-occur with other species at varying abundances. However, applying this mathematical framework to empirical data is still challenging, precluding a larger adoption of the theoretical tools developed by empiricists. This package provides a complete toolbox for modelling interaction effects between species, and calculate fitness and niche differences. The functions are flexible, may accept covariates, and different fitting algorithms can be used. A full description of the underlying methods is available in García-Callejas, D., Godoy, O., and Bartomeus, I. (2020) <doi:10.1111/2041-210X.13443>. Furthermore, the package provides a series of functions to calculate dynamics for stage-structured populations across sites.
Authors:
cxr_1.1.1.tar.gz
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cxr.pdf |cxr.html✨
cxr/json (API)
NEWS
# Install 'cxr' in R: |
install.packages('cxr', repos = c('https://radicalcommecol.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/radicalcommecol/cxr/issues
- abundance - Abundance measurements
- glm_example_coefs - Generalized linear model coefficients
- metapopulation_example_param - Metapopulation dynamics coefficients
- neigh_list - Neighbours and fitness observations
- salinity_list - Salinity measurements
- spatial_sampling - Spatial arrangement of the observations
- species_rates - Species germination and survival rates
Last updated 1 years agofrom:eb37479fff. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 12 2024 |
R-4.5-win | OK | Nov 12 2024 |
R-4.5-linux | OK | Nov 12 2024 |
R-4.4-win | OK | Nov 12 2024 |
R-4.4-mac | OK | Nov 12 2024 |
R-4.3-win | OK | Nov 12 2024 |
R-4.3-mac | OK | Nov 12 2024 |
Exports:abundance_projectionavg_fitness_diffBH_er_lambdacov_global_effectcov_global_responsecov_globalBH_er_lambdacov_none_effectcov_none_responsecov_noneBH_pm_alpha_global_lambdacov_none_alphacov_noneBH_pm_alpha_none_lambdacov_none_alphacov_noneBH_pm_alpha_pairwise_lambdacov_global_alphacov_globalBH_pm_alpha_pairwise_lambdacov_global_alphacov_pairwiseBH_pm_alpha_pairwise_lambdacov_none_alphacov_noneBH_project_alpha_global_lambdacov_none_alphacov_noneBH_project_alpha_none_lambdacov_none_alphacov_noneBH_project_alpha_pairwise_lambdacov_global_alphacov_globalBH_project_alpha_pairwise_lambdacov_global_alphacov_pairwiseBH_project_alpha_pairwise_lambdacov_none_alphacov_nonebuild_paramcalculate_densitiescompetitive_abilitycxr_er_bootstrapcxr_er_fitcxr_generate_test_datacxr_pm_bootstrapcxr_pm_fitcxr_pm_multifitdensities_to_dffill_demography_matrixfill_dispersal_matrixfill_transition_matrixfitness_ratiogenerate_vital_rate_coefsLV_er_lambdacov_global_effectcov_global_responsecov_globalLV_er_lambdacov_none_effectcov_none_responsecov_noneLV_pm_alpha_global_lambdacov_none_alphacov_noneLV_pm_alpha_none_lambdacov_none_alphacov_noneLV_pm_alpha_pairwise_lambdacov_global_alphacov_globalLV_pm_alpha_pairwise_lambdacov_global_alphacov_pairwiseLV_pm_alpha_pairwise_lambdacov_none_alphacov_noneLV_project_alpha_global_lambdacov_none_alphacov_noneLV_project_alpha_none_lambdacov_none_alphacov_noneLV_project_alpha_pairwise_lambdacov_global_alphacov_globalLV_project_alpha_pairwise_lambdacov_global_alphacov_pairwiseLV_project_alpha_pairwise_lambdacov_none_alphacov_noneLW_er_lambdacov_global_effectcov_global_responsecov_globalLW_er_lambdacov_none_effectcov_none_responsecov_noneLW_pm_alpha_global_lambdacov_none_alphacov_noneLW_pm_alpha_none_lambdacov_none_alphacov_noneLW_pm_alpha_pairwise_lambdacov_global_alphacov_globalLW_pm_alpha_pairwise_lambdacov_global_alphacov_pairwiseLW_pm_alpha_pairwise_lambdacov_none_alphacov_noneLW_project_alpha_global_lambdacov_none_alphacov_noneLW_project_alpha_none_lambdacov_none_alphacov_noneLW_project_alpha_pairwise_lambdacov_global_alphacov_globalLW_project_alpha_pairwise_lambdacov_global_alphacov_pairwiseLW_project_alpha_pairwise_lambdacov_none_alphacov_noneniche_overlapRK_er_lambdacov_global_effectcov_global_responsecov_globalRK_er_lambdacov_none_effectcov_none_responsecov_noneRK_pm_alpha_global_lambdacov_none_alphacov_noneRK_pm_alpha_none_lambdacov_none_alphacov_noneRK_pm_alpha_pairwise_lambdacov_global_alphacov_globalRK_pm_alpha_pairwise_lambdacov_global_alphacov_pairwiseRK_pm_alpha_pairwise_lambdacov_none_alphacov_noneRK_project_alpha_global_lambdacov_none_alphacov_noneRK_project_alpha_none_lambdacov_none_alphacov_noneRK_project_alpha_pairwise_lambdacov_global_alphacov_globalRK_project_alpha_pairwise_lambdacov_global_alphacov_pairwiseRK_project_alpha_pairwise_lambdacov_none_alphacov_nonespecies_fitnessvec_permutation_matricesvital_rate
Projecting species abundances
Rendered fromV5_Abundance_projections.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-06-24
Started: 2020-03-26
Coexistence metrics
Rendered fromV3_Coexistence_metrics.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-06-24
Started: 2020-02-28
Data formats
Rendered fromV2_Data_formats.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-03-26
Started: 2020-02-12
Getting started with cxr
Rendered fromV1_Getting_started.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2021-10-03
Started: 2020-03-29
Metapopulation projections
Rendered fromV6_Metapopulation_projections.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2023-03-31
Started: 2022-02-01
Using your own models
Rendered fromV4_Models.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2020-06-24
Started: 2020-03-26