{
  "_id": "6a102995acfb0bcc41c9182d",
  "Type": "Package",
  "Package": "cxr",
  "Title": "A Toolbox for Modelling Species Coexistence in R",
  "Version": "1.1.1",
  "Authors@R": "c(\nperson(\"David\", \"Garcia-Callejas\", , \"david.garcia.callejas@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-6982-476X\")),\nperson(\"Ignasi\", \"Bartomeus\", , \"nacho.bartomeus@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-7893-4389\")),\nperson(\"Oscar\", \"Godoy\", , \"ogodoy.re@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-4988-6626\")),\nperson(\"Maxime\", \"Lancelot\", role = \"ctb\"),\nperson(\"Maria\", \"Paniw\", role = \"ctb\")\n)",
  "Description": "Recent developments in modern coexistence theory have\nadvanced our understanding on how species are able to persist\nand co-occur with other species at varying abundances. However,\napplying this mathematical framework to empirical data is still\nchallenging, precluding a larger adoption of the theoretical\ntools developed by empiricists. This package provides a\ncomplete toolbox for modelling interaction effects between\nspecies, and calculate fitness and niche differences.  The\nfunctions are flexible, may accept covariates, and different\nfitting algorithms can be used.  A full description of the\nunderlying methods is available in García-Callejas, D., Godoy,\nO., and Bartomeus, I. (2020) <doi:10.1111/2041-210X.13443>.\nFurthermore, the package provides a series of functions to\ncalculate dynamics for stage-structured populations across\nsites.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/RadicalCommEcol/cxr",
  "BugReports": "https://github.com/RadicalCommEcol/cxr/issues",
  "VignetteBuilder": "knitr",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.3.2",
  "Config/pak/sysreqs": "cmake",
  "Repository": "https://radicalcommecol.r-universe.dev",
  "Date/Publication": "2025-02-05 10:32:22 UTC",
  "RemoteUrl": "https://github.com/radicalcommecol/cxr",
  "RemoteRef": "HEAD",
  "RemoteSha": "f842189573d6873ea2b15e79fd971d7f8a4ef304",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-13 07:31:16 UTC",
    "User": "root"
  },
  "Author": "David Garcia-Callejas [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-6982-476X>),\nIgnasi Bartomeus [aut] (ORCID: <https://orcid.org/0000-0001-7893-4389>),\nOscar Godoy [aut] (ORCID: <https://orcid.org/0000-0003-4988-6626>),\nMaxime Lancelot [ctb],\nMaria Paniw [ctb]",
  "Maintainer": "David Garcia-Callejas <david.garcia.callejas@gmail.com>",
  "MD5sum": "90d8cb4cdbafd4f7afb61adefb78eba9",
  "_user": "radicalcommecol",
  "_type": "src",
  "_file": "cxr_1.1.1.tar.gz",
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  "_created": "2026-05-13T07:31:16.000Z",
  "_published": "2026-05-22T10:01:57.585Z",
  "_distro": "noble",
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  "_buildurl": "https://github.com/r-universe/radicalcommecol/actions/runs/25784844099",
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  "_upstream": "https://github.com/radicalcommecol/cxr",
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    "id": "f842189573d6873ea2b15e79fd971d7f8a4ef304",
    "author": "garciacallejas <david.garcia.callejas@gmail.com>",
    "committer": "garciacallejas <david.garcia.callejas@gmail.com>",
    "message": "fix small bug on avg_fitness_dif, competitive_ability, niche_overlap, where on the second parameterization the functions would not properly find the model family\n",
    "time": 1738751542
  },
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    "name": "David Garcia-Callejas",
    "email": "david.garcia.callejas@gmail.com",
    "login": "garciacallejas",
    "bluesky": "@callejas.eurosky.social",
    "orcid": "0000-0001-6982-476X",
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      "package": "R",
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      "package": "Matrix",
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      "package": "mvtnorm",
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    "type": "organization",
    "name": "Radical Community Ecology",
    "description": "Bartomeus & Godoy labs join forces to understand community ecology"
  },
  "_downloads": {
    "count": 211,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/cxr"
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  "_devurl": "https://github.com/radicalcommecol/cxr",
  "_searchresults": 26,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
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    "manual.pdf"
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  "_homeurl": "https://github.com/radicalcommecol/cxr",
  "_realowner": "radicalcommecol",
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      "date": "2021-04-16"
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    {
      "version": "1.1.1",
      "date": "2023-10-27"
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  ],
  "_exports": [
    "abundance_projection",
    "avg_fitness_diff",
    "BH_er_lambdacov_global_effectcov_global_responsecov_global",
    "BH_er_lambdacov_none_effectcov_none_responsecov_none",
    "BH_pm_alpha_global_lambdacov_none_alphacov_none",
    "BH_pm_alpha_none_lambdacov_none_alphacov_none",
    "BH_pm_alpha_pairwise_lambdacov_global_alphacov_global",
    "BH_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "BH_pm_alpha_pairwise_lambdacov_none_alphacov_none",
    "BH_project_alpha_global_lambdacov_none_alphacov_none",
    "BH_project_alpha_none_lambdacov_none_alphacov_none",
    "BH_project_alpha_pairwise_lambdacov_global_alphacov_global",
    "BH_project_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "BH_project_alpha_pairwise_lambdacov_none_alphacov_none",
    "build_param",
    "calculate_densities",
    "competitive_ability",
    "cxr_er_bootstrap",
    "cxr_er_fit",
    "cxr_generate_test_data",
    "cxr_pm_bootstrap",
    "cxr_pm_fit",
    "cxr_pm_multifit",
    "densities_to_df",
    "fill_demography_matrix",
    "fill_dispersal_matrix",
    "fill_transition_matrix",
    "fitness_ratio",
    "generate_vital_rate_coefs",
    "LV_er_lambdacov_global_effectcov_global_responsecov_global",
    "LV_er_lambdacov_none_effectcov_none_responsecov_none",
    "LV_pm_alpha_global_lambdacov_none_alphacov_none",
    "LV_pm_alpha_none_lambdacov_none_alphacov_none",
    "LV_pm_alpha_pairwise_lambdacov_global_alphacov_global",
    "LV_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "LV_pm_alpha_pairwise_lambdacov_none_alphacov_none",
    "LV_project_alpha_global_lambdacov_none_alphacov_none",
    "LV_project_alpha_none_lambdacov_none_alphacov_none",
    "LV_project_alpha_pairwise_lambdacov_global_alphacov_global",
    "LV_project_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "LV_project_alpha_pairwise_lambdacov_none_alphacov_none",
    "LW_er_lambdacov_global_effectcov_global_responsecov_global",
    "LW_er_lambdacov_none_effectcov_none_responsecov_none",
    "LW_pm_alpha_global_lambdacov_none_alphacov_none",
    "LW_pm_alpha_none_lambdacov_none_alphacov_none",
    "LW_pm_alpha_pairwise_lambdacov_global_alphacov_global",
    "LW_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "LW_pm_alpha_pairwise_lambdacov_none_alphacov_none",
    "LW_project_alpha_global_lambdacov_none_alphacov_none",
    "LW_project_alpha_none_lambdacov_none_alphacov_none",
    "LW_project_alpha_pairwise_lambdacov_global_alphacov_global",
    "LW_project_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "LW_project_alpha_pairwise_lambdacov_none_alphacov_none",
    "niche_overlap",
    "RK_er_lambdacov_global_effectcov_global_responsecov_global",
    "RK_er_lambdacov_none_effectcov_none_responsecov_none",
    "RK_pm_alpha_global_lambdacov_none_alphacov_none",
    "RK_pm_alpha_none_lambdacov_none_alphacov_none",
    "RK_pm_alpha_pairwise_lambdacov_global_alphacov_global",
    "RK_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "RK_pm_alpha_pairwise_lambdacov_none_alphacov_none",
    "RK_project_alpha_global_lambdacov_none_alphacov_none",
    "RK_project_alpha_none_lambdacov_none_alphacov_none",
    "RK_project_alpha_pairwise_lambdacov_global_alphacov_global",
    "RK_project_alpha_pairwise_lambdacov_global_alphacov_pairwise",
    "RK_project_alpha_pairwise_lambdacov_none_alphacov_none",
    "species_fitness",
    "vec_permutation_matrices",
    "vital_rate"
  ],
  "_datasets": [
    {
      "name": "abundance",
      "title": "Abundance measurements",
      "object": "abundance",
      "file": "abundance.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "plot",
        "subplot",
        "species",
        "individuals"
      ],
      "rows": 5508,
      "table": true,
      "tojson": true
    },
    {
      "name": "glm_example_coefs",
      "title": "Generalized linear model coefficients",
      "object": "glm_example_coefs",
      "file": "glm_example_coefs.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "Estimate",
        "Std. Error",
        "z value",
        "Pr(>|z|)"
      ],
      "rows": 8,
      "table": true,
      "tojson": true
    },
    {
      "name": "metapopulation_example_param",
      "title": "Metapopulation dynamics coefficients",
      "object": "metapopulation_example_param",
      "file": "metapopulation_example_param.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
    {
      "name": "neigh_list",
      "title": "neighbours and fitness observations",
      "object": "neigh_list",
      "file": "neigh_list.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
    {
      "name": "salinity_list",
      "title": "Salinity measurements",
      "object": "salinity_list",
      "file": "salinity_list.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
    {
      "name": "spatial_sampling",
      "title": "spatial arrangement of the observations",
      "object": "spatial_sampling",
      "file": "spatial_sampling.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
    {
      "name": "species_rates",
      "title": "Species germination and survival rates",
      "object": "species_rates",
      "file": "species_rates.RData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "code",
        "species",
        "germination.rate",
        "seed.survival"
      ],
      "rows": 17,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "abundance",
      "title": "Abundance measurements",
      "topics": [
        "abundance"
      ]
    },
    {
      "page": "abundance_projection",
      "title": "Project abundances from population dynamics models",
      "topics": [
        "abundance_projection"
      ]
    },
    {
      "page": "avg_fitness_diff",
      "title": "Average fitness differences",
      "topics": [
        "avg_fitness_diff"
      ]
    },
    {
      "page": "BH_er_lambdacov_global_effectcov_global_responsecov_global",
      "title": "Effect response Beverton-Holt model with covariate effects on lambda, effect, and response",
      "topics": [
        "BH_er_lambdacov_global_effectcov_global_responsecov_global"
      ]
    },
    {
      "page": "BH_er_lambdacov_none_effectcov_none_responsecov_none",
      "title": "Effect response model without covariate effects",
      "topics": [
        "BH_er_lambdacov_none_effectcov_none_responsecov_none"
      ]
    },
    {
      "page": "BH_pm_alpha_global_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model with a global alpha and no covariate effects",
      "topics": [
        "BH_pm_alpha_global_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "BH_pm_alpha_none_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model with no alphas and no covariate effects",
      "topics": [
        "BH_pm_alpha_none_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "BH_pm_alpha_pairwise_lambdacov_global_alphacov_global",
      "title": "Beverton-Holt model with pairwise alphas and global covariate effects on lambda and alpha",
      "topics": [
        "BH_pm_alpha_pairwise_lambdacov_global_alphacov_global"
      ]
    },
    {
      "page": "BH_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise",
      "title": "Beverton-Holt model with pairwise alphas, covariate effects on lambda, and pairwise covariate effects on alpha",
      "topics": [
        "BH_pm_alpha_pairwise_lambdacov_global_alphacov_pairwise"
      ]
    },
    {
      "page": "BH_pm_alpha_pairwise_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model with pairwise alphas and no covariate effects",
      "topics": [
        "BH_pm_alpha_pairwise_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "BH_project_alpha_global_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model for projecting abundances, with a global alpha and no covariate effects",
      "topics": [
        "BH_project_alpha_global_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "BH_project_alpha_none_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model for projecting abundances, with no alpha and no covariate effects",
      "topics": [
        "BH_project_alpha_none_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "BH_project_alpha_pairwise_lambdacov_global_alphacov_global",
      "title": "Beverton-Holt model for projecting abundances, with specific alpha values and global covariate effects on alpha and lambda",
      "topics": [
        "BH_project_alpha_pairwise_lambdacov_global_alphacov_global"
      ]
    },
    {
      "page": "BH_project_alpha_pairwise_lambdacov_global_alphacov_pairwise",
      "title": "Beverton-Holt model for projecting abundances, with specific alpha values and global covariate effects on alpha and lambda",
      "topics": [
        "BH_project_alpha_pairwise_lambdacov_global_alphacov_pairwise"
      ]
    },
    {
      "page": "BH_project_alpha_pairwise_lambdacov_none_alphacov_none",
      "title": "Beverton-Holt model for projecting abundances, with specific alpha values and no covariate effects",
      "topics": [
        "BH_project_alpha_pairwise_lambdacov_none_alphacov_none"
      ]
    },
    {
      "page": "build_param",
      "title": "Build param structure",
      "topics": [
        "build_param"
      ]
    },
    {
      "page": "calculate_densities",
      "title": "Obtain species densities from transition matrices",
      "topics": [
        "calculate_densities"
      ]
    },
    {
      "page": "competitive_ability",
      "title": "Competitive ability among pairs of species",
      "topics": [
        "competitive_ability"
      ]
    },
    {
      "page": "cxr_er_bootstrap",
      "title": "standard error estimates for effect and response parameters",
      "topics": [
        "cxr_er_bootstrap"
      ]
    },
    {
      "page": "cxr_er_fit",
      "title": "General optimization for effect-response models",
      "topics": [
        "cxr_er_fit"
      ]
    },
    {
      "page": "cxr_generate_test_data",
      "title": "Generate simulated interaction data",
      "topics": [
        "cxr_generate_test_data"
      ]
    },
    {
      "page": "cxr_pm_bootstrap",
      "title": "Standard error estimates for model parameters",
      "topics": [
        "cxr_pm_bootstrap"
      ]
    },
    {
      "page": "cxr_pm_fit",
      "title": "General optimization for population models",
      "topics": [
        "cxr_pm_fit"
      ]
    },
    {
      "page": "cxr_pm_multifit",
      "title": "Multi-species parameter optimization",
      "topics": [
        "cxr_pm_multifit"
      ]
    },
    {
      "page": "densities_to_df",
      "title": "Converts a densities list to a tidy dataframe",
      "topics": [
        "densities_to_df"
      ]
    },
    {
      "page": "fill_demography_matrix",
      "title": "Fill the vec-permutation demography matrix",
      "topics": [
        "fill_demography_matrix"
      ]
    },
    {
      "page": "fill_dispersal_matrix",
      "title": "Fill the vec-permutation dispersal matrix",
      "topics": [
        "fill_dispersal_matrix"
      ]
    },
    {
      "page": "fill_transition_matrix",
      "title": "Fill a transition matrix",
      "topics": [
        "fill_transition_matrix"
      ]
    },
    {
      "page": "fitness_ratio",
      "title": "Fitness ratio among two or more species",
      "topics": [
        "fitness_ratio"
      ]
    },
    {
      "page": "generate_vital_rate_coefs",
      "title": "Generate coefficients for obtaining vital rates",
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