{
  "_id": "6ae289b595ca2370cc8ccdda",
  "Type": "Package",
  "Package": "gllvmTMB",
  "Title": "Generalised Linear Latent Variable Models",
  "Version": "0.7.1",
  "Authors@R": "person(\"Shinichi\", \"Nakagawa\", , \"itchyshin@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-7765-5182\"))",
  "Description": "Fits multivariate generalised linear latent variable\nmodels using either long-format data or a wide data frame.\nModels support several response distributions and trait\ncovariance structures, and can estimate correlations, shared\nlatent axes, and trait-specific variances. Binary\npresence-absence data can be used for joint species\ndistribution analyses. Optional animal, phylogenetic, spatial,\nand kernel covariance components are available. Estimation uses\n'Template Model Builder'. Spatial effects can use sparse\nGaussian Markov random field constructions. This 0.7.1 release\nremains experimental: evidence for estimates is model- and\nregime-specific. Broad interval coverage is not certified; a\n0.94 coverage floor is documented only for one two-sided\nGaussian total-variance profile setting.",
  "License": "GPL-3",
  "Language": "en-GB",
  "Copyright": "inst/COPYRIGHTS",
  "URL": "https://itchyshin.github.io/gllvmTMB/,\nhttps://github.com/itchyshin/gllvmTMB",
  "BugReports": "https://github.com/itchyshin/gllvmTMB/issues",
  "VignetteBuilder": "knitr",
  "ByteCompile": "true",
  "Config/testthat/edition": "3",
  "Config/testthat/parallel": "true",
  "Encoding": "UTF-8",
  "SystemRequirements": "GNU make, C++17",
  "Config/roxygen2/version": "8.0.0",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-10-28 23:34:33 UTC",
    "User": "root"
  },
  "Author": "Shinichi Nakagawa [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-7765-5182>)",
  "Maintainer": "Shinichi Nakagawa <itchyshin@gmail.com>",
  "Config/pak/sysreqs": "make",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-10-28 21:45:14 UTC",
  "RemoteUrl": "https://github.com/cran/gllvmTMB",
  "RemoteRef": "HEAD",
  "RemoteSha": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
  "_user": "cran",
  "_type": "src",
  "_file": "gllvmTMB_0.7.1.tar.gz",
  "_fileid": "https://r2.ropensci.org/accf9d57416bc092d43414b65e18304a1d138bd44dfec5c2f8455de22b4a3d7e",
  "_filesize": 5706935,
  "_sha256": "accf9d57416bc092d43414b65e18304a1d138bd44dfec5c2f8455de22b4a3d7e",
  "_expires": "2027-02-05T23:48:03.000Z",
  "_created": "2026-10-28T23:34:33.000Z",
  "_published": "2026-10-28T23:48:05.870Z",
  "_upstream": "https://github.com/cran/gllvmTMB",
  "_status": "success",
  "_maintainer": {
    "name": "Shinichi Nakagawa",
    "email": "itchyshin@gmail.com",
    "login": "itchyshin",
    "orcid": "0000-0002-7765-5182",
    "description": "An evolutionary biologist (with some Darwinian fitness in his arms), trying to learn how to use Git and R together. ",
    "uuid": 12078523
  },
  "_jobs": [
    {
      "job": 123168226915,
      "time": 373,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "12860817312"
    },
    {
      "job": 123168226739,
      "time": 439,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "12860658055"
    },
    {
      "job": 123168226757,
      "time": 349,
      "config": "linux-release-arm64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "12861280546"
    },
    {
      "job": 123168226774,
      "time": 439,
      "config": "linux-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "12861250898"
    },
    {
      "job": 123164237345,
      "time": 625,
      "config": "source",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "12860187604"
    },
    {
      "job": 123168226848,
      "time": 245,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "12861140766"
    },
    {
      "job": 123168226760,
      "time": 485,
      "config": "windows-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "12860039739"
    },
    {
      "job": 123168226769,
      "time": 476,
      "config": "windows-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "12861071474"
    },
    {
      "job": 123168226794,
      "time": 522,
      "config": "windows-release-arm64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "12860683228"
    },
    {
      "job": 123168226779,
      "time": 484,
      "config": "windows-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "12861460283"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932",
  "_commit": {
    "id": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
    "author": "Shinichi Nakagawa <itchyshin@gmail.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.7.1\n",
    "time": 1793223914
  },
  "_distro": "resolute",
  "_host": "GitHub-Actions",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.1.0",
      "role": "Depends"
    },
    {
      "package": "BH",
      "role": "LinkingTo"
    },
    {
      "package": "RcppEigen",
      "role": "LinkingTo"
    },
    {
      "package": "TMB",
      "role": "LinkingTo"
    },
    {
      "package": "assertthat",
      "role": "Imports"
    },
    {
      "package": "cli",
      "role": "Imports"
    },
    {
      "package": "fmesher",
      "role": "Imports"
    },
    {
      "package": "generics",
      "role": "Imports"
    },
    {
      "package": "graphics",
      "role": "Imports"
    },
    {
      "package": "lifecycle",
      "role": "Imports"
    },
    {
      "package": "Matrix",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "rlang",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "tidyselect",
      "role": "Imports"
    },
    {
      "package": "TMB",
      "version": ">= 1.8.0",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "ape",
      "role": "Suggests"
    },
    {
      "package": "DHARMa",
      "role": "Suggests"
    },
    {
      "package": "detectseparation",
      "version": ">= 0.4.0",
      "role": "Suggests"
    },
    {
      "package": "dplyr",
      "role": "Suggests"
    },
    {
      "package": "future",
      "role": "Suggests"
    },
    {
      "package": "future.apply",
      "role": "Suggests"
    },
    {
      "package": "ggforce",
      "role": "Suggests"
    },
    {
      "package": "ggplot2",
      "role": "Suggests"
    },
    {
      "package": "galamm",
      "role": "Suggests"
    },
    {
      "package": "glmmTMB",
      "role": "Suggests"
    },
    {
      "package": "gllvm",
      "role": "Suggests"
    },
    {
      "package": "JuliaCall",
      "role": "Suggests"
    },
    {
      "package": "jsonlite",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "lme4",
      "role": "Suggests"
    },
    {
      "package": "MASS",
      "role": "Suggests"
    },
    {
      "package": "MCMCglmm",
      "role": "Suggests"
    },
    {
      "package": "mgcv",
      "role": "Suggests"
    },
    {
      "package": "mirt",
      "role": "Suggests"
    },
    {
      "package": "mvtnorm",
      "role": "Suggests"
    },
    {
      "package": "nadiv",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "sf",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 3.0.0",
      "role": "Suggests"
    },
    {
      "package": "tibble",
      "role": "Suggests"
    },
    {
      "package": "tidyr",
      "role": "Suggests"
    },
    {
      "package": "tweedie",
      "role": "Suggests"
    },
    {
      "package": "vegan",
      "role": "Suggests"
    },
    {
      "package": "vdiffr",
      "role": "Suggests"
    },
    {
      "package": "withr",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-44",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "0.7.1",
      "date": "2026-10-28"
    }
  ],
  "_stars": 0,
  "_contributors": [
    {
      "user": "itchyshin",
      "count": 1,
      "uuid": 12078523
    }
  ],
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "followers": 634,
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 0,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/gllvmTMB"
  },
  "_devurl": "https://github.com/itchyshin/gllvmtmb",
  "_pkgdown": "https://itchyshin.github.io/gllvmTMB/",
  "_searchresults": 298,
  "_topics": [
    "cpp"
  ],
  "_rbuild": "4.6.1",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/gllvmTMB.html",
    "extra/manual.pdf",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md"
  ],
  "_cranurl": false,
  "_releases": [
    {
      "version": "0.7.1",
      "date": "2026-10-28"
    }
  ],
  "_exports": [
    ".proportions_bootstrap_ci",
    ".proportions_wald_ci",
    "add_utm_columns",
    "animal_dep",
    "animal_indep",
    "animal_latent",
    "animal_scalar",
    "animal_slope",
    "animal_unique",
    "Beta",
    "betabinomial",
    "block_V",
    "bootstrap_Sigma",
    "categorical",
    "censored_poisson",
    "check_auto_residual",
    "check_gllvmTMB",
    "compare_dep_vs_two_psi",
    "compare_indep_vs_two_psi",
    "compare_loadings",
    "compare_Sigma_table",
    "confint_inspect",
    "confirmatory_lambda",
    "cumulative_logit",
    "delta_beta",
    "delta_gamma",
    "delta_gamma_mix",
    "delta_gengamma",
    "delta_lognormal",
    "delta_lognormal_mix",
    "delta_poisson_link_gamma",
    "delta_poisson_link_lognormal",
    "delta_truncated_nbinom1",
    "delta_truncated_nbinom2",
    "dep",
    "diagnose_kernel_separability",
    "diagnostic_table",
    "extract_coevolution_modules",
    "extract_communality",
    "extract_correlations",
    "extract_cross_correlations",
    "extract_cutpoints",
    "extract_Gamma",
    "extract_ICC_site",
    "extract_loadings",
    "extract_lv_effects",
    "extract_Omega",
    "extract_ordination",
    "extract_phylo_signal",
    "extract_proportions",
    "extract_repeatability",
    "extract_residual_cor",
    "extract_residual_cov",
    "extract_residual_split",
    "extract_rotated_loadings_table",
    "extract_Sigma",
    "extract_Sigma_B",
    "extract_Sigma_table",
    "extract_Sigma_W",
    "flag_unreliable_loadings",
    "gamma_mix",
    "gengamma",
    "get_crs",
    "getLoadings",
    "getLV",
    "getREsd",
    "getResidualCor",
    "getResidualCov",
    "gllvm_julia_fit",
    "gllvm_julia_setup",
    "gllvmTMB",
    "gllvmTMB_check_consistency",
    "gllvmTMB_diagnose",
    "gllvmTMB_wide",
    "gllvmTMBcontrol",
    "gr",
    "impute_model",
    "imputed",
    "indep",
    "isdm_source",
    "isdm_sources",
    "kernel_dep",
    "kernel_indep",
    "kernel_latent",
    "kernel_scalar",
    "kernel_unique",
    "latent",
    "loading_ci",
    "loading_profile",
    "lognormal",
    "lognormal_mix",
    "make_cross_kernel",
    "make_mesh",
    "meta",
    "meta_known_V",
    "meta_V",
    "miss_control",
    "multinomial",
    "nbinom1",
    "nbinom2",
    "nbinom2_mix",
    "ordinal_probit",
    "ordiplot",
    "pedigree_to_A",
    "pedigree_to_Ainv_sparse",
    "phylo",
    "phylo_dep",
    "phylo_indep",
    "phylo_latent",
    "phylo_rr",
    "phylo_scalar",
    "phylo_signal_mi",
    "phylo_slope",
    "phylo_unique",
    "plot_anisotropy",
    "plot_anisotropy2",
    "plot_correlations",
    "plot_loadings_confidence_eye",
    "plot_rotated_loadings",
    "plot_Sigma_comparison",
    "plot_Sigma_heatmap",
    "plot_Sigma_table",
    "predict_cross_covariance",
    "predict_missing",
    "predictive_check",
    "profile_ci_phylo_signal",
    "profile_ci_total_variance",
    "profile_cross_rho",
    "profile_cross_rho_ci",
    "profile_phylo_signal",
    "profile_targets",
    "ridge_path",
    "rotate_loadings",
    "sanity_multi",
    "scalar",
    "screen_control",
    "screen_gllvmTMB",
    "screen_table",
    "simulate_site_trait",
    "simulate_unit_trait",
    "slope_sd_ci",
    "spatial",
    "spatial_dep",
    "spatial_indep",
    "spatial_latent",
    "spatial_scalar",
    "spatial_unique",
    "spde",
    "standard_errors",
    "student",
    "suggest_lambda_constraint",
    "suggest_lambda_constraints",
    "tidy",
    "tmbprofile_wrapper",
    "traits",
    "truncated_nbinom1",
    "truncated_nbinom2",
    "truncated_poisson",
    "tweedie",
    "VP"
  ],
  "_help": [
    {
      "page": "add_utm_columns",
      "title": "Add UTM coordinates to a data frame",
      "topics": [
        "add_utm_columns"
      ]
    },
    {
      "page": "animal_dep",
      "title": "Full unstructured animal-model trait covariance: 'animal_dep(0 + trait | id)'",
      "topics": [
        "animal_dep"
      ]
    },
    {
      "page": "animal_indep",
      "title": "Independent per-trait animal-model random intercepts: 'animal_indep(0 + trait | id)'",
      "topics": [
        "animal_indep"
      ]
    },
    {
      "page": "animal_latent",
      "title": "Reduced-rank animal-model latent factors: 'animal_latent(id, d = K)'",
      "topics": [
        "animal_latent"
      ]
    },
    {
      "page": "animal_scalar",
      "title": "Single-shared-variance animal-model random effect: 'animal_scalar(id)'",
      "topics": [
        "animal_scalar"
      ]
    },
    {
      "page": "animal_slope",
      "title": "Animal-model random slope on a continuous covariate",
      "topics": [
        "animal_slope"
      ]
    },
    {
      "page": "animal_unique",
      "title": "Per-trait independent animal-model random intercepts: 'animal_unique(id)'",
      "topics": [
        "animal_unique"
      ]
    },
    {
      "page": "block_V",
      "title": "Build a block-diagonal sampling-variance matrix V",
      "topics": [
        "block_V"
      ]
    },
    {
      "page": "bootstrap_Sigma",
      "title": "Bootstrap covariance, correlation, communality, and ICC summaries",
      "topics": [
        "bootstrap_Sigma"
      ]
    },
    {
      "page": "categorical",
      "title": "Baseline-category softmax unordered categorical missing-predictor family",
      "topics": [
        "categorical"
      ]
    },
    {
      "page": "check_auto_residual",
      "title": "Check whether 'link_residual = \"auto\"' is coherent for this fit",
      "topics": [
        "check_auto_residual"
      ]
    },
    {
      "page": "check_gllvmTMB",
      "title": "Check convergence, Hessian, gradients, and interval readiness",
      "topics": [
        "check_gllvmTMB"
      ]
    },
    {
      "page": "compare_dep_vs_two_psi",
      "title": "Canonical likelihood-based cross-check for the paired phylogenetic decomposition",
      "topics": [
        "compare_dep_vs_two_psi"
      ]
    },
    {
      "page": "compare_indep_vs_two_psi",
      "title": "Cheap diagonal cross-check for the paired phylogenetic decomposition (large T)",
      "topics": [
        "compare_indep_vs_two_psi"
      ]
    },
    {
      "page": "compare_loadings",
      "title": "Compare two loading matrices after Procrustes alignment",
      "topics": [
        "compare_loadings"
      ]
    },
    {
      "page": "compare_Sigma_table",
      "title": "Compare fitted Sigma-table rows with a known truth matrix",
      "topics": [
        "compare_Sigma_table"
      ]
    },
    {
      "page": "confint_inspect",
      "title": "Inspect profile confidence-interval shape for a fitted model",
      "topics": [
        "confint_inspect"
      ]
    },
    {
      "page": "confint.gllvmTMB_multi",
      "title": "Confidence intervals for a fitted gllvmTMB model",
      "topics": [
        "confint.gllvmTMB_multi"
      ]
    },
    {
      "page": "confirmatory_lambda",
      "title": "Build a confirmatory 'lambda_constraint' matrix from group membership",
      "topics": [
        "confirmatory_lambda"
      ]
    },
    {
      "page": "cumulative_logit",
      "title": "Cumulative-logit ordered categorical missing-predictor family",
      "topics": [
        "cumulative_logit"
      ]
    },
    {
      "page": "dep",
      "title": "Full unstructured trait covariance: 'dep(0 + trait | g)'",
      "topics": [
        "dep"
      ]
    },
    {
      "page": "deviance.gllvmTMB_multi",
      "title": "Deviance of a fitted gllvmTMB model",
      "topics": [
        "deviance.gllvmTMB_multi"
      ]
    },
    {
      "page": "diagnose_kernel_separability",
      "title": "Diagnose fixed-kernel separability before fitting",
      "topics": [
        "diagnose_kernel_separability"
      ]
    },
    {
      "page": "diagnostic_table",
      "title": "Extract report-ready tables from diagnostic objects",
      "topics": [
        "diagnostic_table"
      ]
    },
    {
      "page": "extract_coevolution_modules",
      "title": "Extract cross-lineage coevolutionary modules",
      "topics": [
        "extract_coevolution_modules"
      ]
    },
    {
      "page": "extract_communality",
      "title": "Communality of each trait",
      "topics": [
        "extract_communality"
      ]
    },
    {
      "page": "extract_correlations",
      "title": "Extract cross-trait correlations",
      "topics": [
        "extract_correlations"
      ]
    },
    {
      "page": "extract_cross_correlations",
      "title": "Cross-family correlations between a nominal (multinomial) trait and partners",
      "topics": [
        "extract_cross_correlations"
      ]
    },
    {
      "page": "extract_cutpoints",
      "title": "Extract ordinal-probit cutpoints from a fitted gllvmTMB model",
      "topics": [
        "extract_cutpoints"
      ]
    },
    {
      "page": "extract_Gamma",
      "title": "Extract a cross-lineage Gamma block",
      "topics": [
        "extract_Gamma"
      ]
    },
    {
      "page": "extract_loadings",
      "title": "Extract the trait loading matrix",
      "topics": [
        "extract_loadings"
      ]
    },
    {
      "page": "extract_lv_effects",
      "title": "Predictor effects on latent-score means",
      "topics": [
        "extract_lv_effects"
      ]
    },
    {
      "page": "extract_Omega",
      "title": "Total trait covariance Omega summed across requested tiers",
      "topics": [
        "extract_Omega"
      ]
    },
    {
      "page": "extract_ordination",
      "title": "Extract ordination scores and loadings from a fitted multivariate model",
      "topics": [
        "extract_ordination"
      ]
    },
    {
      "page": "extract_phylo_signal",
      "title": "Phylogenetic-signal proportions per trait",
      "topics": [
        "extract_phylo_signal"
      ]
    },
    {
      "page": "extract_proportions",
      "title": "Per-trait proportion-of-variance decomposition across all model components",
      "topics": [
        "extract_proportions"
      ]
    },
    {
      "page": "extract_repeatability",
      "title": "Per-trait repeatability with confidence intervals",
      "topics": [
        "extract_repeatability"
      ]
    },
    {
      "page": "extract_residual_cov",
      "title": "Implied trait covariance or correlation",
      "topics": [
        "extract_residual_cor",
        "extract_residual_cov"
      ]
    },
    {
      "page": "extract_rotated_loadings_table",
      "title": "Extract a tidy rotated loading table",
      "topics": [
        "extract_rotated_loadings_table"
      ]
    },
    {
      "page": "extract_Sigma",
      "title": "Extract the implied trait covariance / correlation at one tier",
      "topics": [
        "extract_Sigma"
      ]
    },
    {
      "page": "extract_Sigma_table",
      "title": "Extract a report-ready table of Sigma or correlation entries",
      "topics": [
        "extract_Sigma_table"
      ]
    },
    {
      "page": "fitted.gllvmTMB_multi",
      "title": "Fitted values from a fitted gllvmTMB model",
      "topics": [
        "fitted.gllvmTMB_multi"
      ]
    },
    {
      "page": "flag_unreliable_loadings",
      "title": "Flag loadings whose CI overlaps a \"biologically negligible\" region",
      "topics": [
        "flag_unreliable_loadings"
      ]
    },
    {
      "page": "get_crs",
      "title": "Infer a UTM coordinate reference system",
      "topics": [
        "get_crs"
      ]
    },
    {
      "page": "gllvm_julia_fit",
      "title": "Fit a GLLVM with the Julia engine (GLLVM.jl 'bridge_fit').",
      "topics": [
        "gllvm_julia_fit"
      ]
    },
    {
      "page": "gllvm_julia_setup",
      "title": "Set up JuliaCall and load the GLLVM.jl engine (once per R session).",
      "topics": [
        "gllvm_julia_setup"
      ]
    },
    {
      "page": "gllvmTMB",
      "title": "Fit multivariate response models from wide or long data",
      "topics": [
        "gllvmTMB"
      ]
    },
    {
      "page": "gllvmTMB_check_consistency",
      "title": "Run an advanced Laplace-consistency check",
      "topics": [
        "gllvmTMB_check_consistency"
      ]
    },
    {
      "page": "gllvmTMB_diagnose",
      "title": "Diagnose a fitted model and suggest next actions",
      "topics": [
        "gllvmTMB_diagnose"
      ]
    },
    {
      "page": "gllvmTMB_julia-methods",
      "title": "Methods for Julia bridge fits",
      "topics": [
        "coef.gllvmTMB_julia",
        "confint.gllvmTMB_julia",
        "fitted.gllvmTMB_julia",
        "gllvmTMB_julia-methods",
        "logLik.gllvmTMB_julia",
        "predict.gllvmTMB_julia",
        "print.gllvmTMB_julia",
        "print.summary.gllvmTMB_julia",
        "residuals.gllvmTMB_julia",
        "simulate.gllvmTMB_julia",
        "summary.gllvmTMB_julia"
      ]
    },
    {
      "page": "gllvmTMB_multi-methods",
      "title": "Methods on a fitted gllvmTMB model",
      "topics": [
        "gllvmTMB_multi-methods",
        "logLik.gllvmTMB_multi",
        "nobs.gllvmTMB_multi",
        "print.gllvmTMB_multi",
        "print.summary.gllvmTMB_multi",
        "summary.gllvmTMB_multi"
      ]
    },
    {
      "page": "gllvmTMB_multi-vcov",
      "title": "Fixed-effect estimates and covariance for a multi-trait fit",
      "topics": [
        "coef.gllvmTMB_multi",
        "gllvmTMB_multi-vcov",
        "vcov.gllvmTMB_multi"
      ]
    },
    {
      "page": "gllvmTMB_va-methods",
      "title": "Methods for variational ('integration = \"va\"') fits",
      "topics": [
        "coef.gllvmTMB_va",
        "confint.gllvmTMB_va",
        "deviance.gllvmTMB_va",
        "df.residual.gllvmTMB_va",
        "fitted.gllvmTMB_va",
        "gllvmTMB_va-methods",
        "logLik.gllvmTMB_va",
        "nobs.gllvmTMB_va",
        "predict.gllvmTMB_va",
        "print.gllvmTMB_va",
        "print.summary.gllvmTMB_va",
        "residuals.gllvmTMB_va",
        "summary.gllvmTMB_va",
        "vcov.gllvmTMB_va",
        "weights.gllvmTMB_va"
      ]
    },
    {
      "page": "gllvmTMBcontrol",
      "title": "Control parameters for 'gllvmTMB()'",
      "topics": [
        "gllvmTMBcontrol"
      ]
    },
    {
      "page": "impute_model",
      "title": "Predictor model for a missing covariate used inside 'mi()'",
      "topics": [
        "impute_model",
        "mi",
        "mi_group"
      ]
    },
    {
      "page": "imputed",
      "title": "Extract fitted missing-predictor values from a 'gllvmTMB' fit",
      "topics": [
        "imputed",
        "imputed.gllvmTMB"
      ]
    },
    {
      "page": "indep",
      "title": "Per-trait marginal variance: 'indep(0 + trait | g)'",
      "topics": [
        "indep"
      ]
    },
    {
      "page": "isdm_source",
      "title": "Declare one iSDM source observation model",
      "topics": [
        "isdm_source"
      ]
    },
    {
      "page": "isdm_sources",
      "title": "Declare the sources of a multi-source integrated model",
      "topics": [
        "isdm_sources"
      ]
    },
    {
      "page": "kernel_latent",
      "title": "Generic dense-kernel covariance keywords",
      "topics": [
        "kernel_dep",
        "kernel_indep",
        "kernel_latent"
      ]
    },
    {
      "page": "kernel_scalar",
      "title": "Dense-kernel one-shared-variance covariance: 'kernel_scalar()'",
      "topics": [
        "kernel_scalar"
      ]
    },
    {
      "page": "kernel_unique",
      "title": "Deprecated alias: 'kernel_unique()'",
      "topics": [
        "kernel_unique"
      ]
    },
    {
      "page": "latent",
      "title": "Latent-factor (reduced-rank) random effect: 'latent(0 + trait | g, d = K)'",
      "topics": [
        "latent"
      ]
    },
    {
      "page": "loading_ci",
      "title": "Confidence intervals on individual entries of the loading matrix",
      "topics": [
        "loading_ci"
      ]
    },
    {
      "page": "loading_profile",
      "title": "Profile-likelihood curve(s) for entries of the loading matrix",
      "topics": [
        "loading_profile"
      ]
    },
    {
      "page": "make_cross_kernel",
      "title": "Build a cross-lineage relatedness kernel",
      "topics": [
        "make_cross_kernel"
      ]
    },
    {
      "page": "make_mesh",
      "title": "Construct an SPDE mesh for gllvmTMB",
      "topics": [
        "make_mesh"
      ]
    },
    {
      "page": "meta_V",
      "title": "Known-V meta-analytic random effect (canonical name): 'meta_V(V = V)'",
      "topics": [
        "meta_V"
      ]
    },
    {
      "page": "miss_control",
      "title": "Missing-data control for 'gllvmTMB()'",
      "topics": [
        "miss_control"
      ]
    },
    {
      "page": "multinomial",
      "title": "Multinomial (baseline-category logit) family",
      "topics": [
        "multinomial"
      ]
    },
    {
      "page": "ordinal_probit",
      "title": "Ordinal-probit threshold family for the multivariate engine",
      "topics": [
        "ordinal_probit"
      ]
    },
    {
      "page": "pedigree_to_A",
      "title": "Pedigree to additive-genetic relatedness matrix 'A'",
      "topics": [
        "pedigree_to_A"
      ]
    },
    {
      "page": "pedigree_to_Ainv_sparse",
      "title": "Sparse pedigree inverse-A via Henderson-Quaas (MCMCglmm-free)",
      "topics": [
        "pedigree_to_Ainv_sparse"
      ]
    },
    {
      "page": "phylo",
      "title": "Phylogenetic random effect: lme4-bar mode-dispatch wrapper",
      "topics": [
        "phylo"
      ]
    },
    {
      "page": "phylo_dep",
      "title": "Full unstructured phylogenetic trait covariance: 'phylo_dep(0 + trait | species)'",
      "topics": [
        "phylo_dep"
      ]
    },
    {
      "page": "phylo_indep",
      "title": "Per-trait phylogenetic marginal variance: 'phylo_indep(0 + trait | species)'",
      "topics": [
        "phylo_indep"
      ]
    },
    {
      "page": "phylo_latent",
      "title": "Reduced-rank phylogenetic latent factors: 'phylo_latent(species, d = K)'",
      "topics": [
        "phylo_latent"
      ]
    },
    {
      "page": "phylo_scalar",
      "title": "Single-shared-variance phylogenetic random effect: 'phylo_scalar(species)'",
      "topics": [
        "phylo_scalar"
      ]
    },
    {
      "page": "phylo_signal_mi",
      "title": "Phylogenetic-signal diagnostic for a modelled missing predictor",
      "topics": [
        "phylo_signal_mi"
      ]
    },
    {
      "page": "phylo_slope",
      "title": "Phylogenetic random slope on a continuous covariate",
      "topics": [
        "phylo_slope"
      ]
    },
    {
      "page": "phylo_unique",
      "title": "Per-trait independent phylogenetic random intercepts: 'phylo_unique(species)'",
      "topics": [
        "phylo_unique"
      ]
    },
    {
      "page": "plot_anisotropy",
      "title": "Plot the isotropic spatial range from a gllvmTMB model",
      "topics": [
        "plot_anisotropy",
        "plot_anisotropy2"
      ]
    },
    {
      "page": "plot_correlations",
      "title": "Plot pairwise trait correlations with intervals",
      "topics": [
        "plot_correlations"
      ]
    },
    {
      "page": "plot_loadings_confidence_eye",
      "title": "Confidence Eye plot for per-species loading uncertainty",
      "topics": [
        "plot_loadings_confidence_eye"
      ]
    },
    {
      "page": "plot_rotated_loadings",
      "title": "Plot a rotated loading matrix",
      "topics": [
        "plot_rotated_loadings"
      ]
    },
    {
      "page": "plot_Sigma_comparison",
      "title": "Plot Sigma-table estimates against a known truth matrix",
      "topics": [
        "plot_Sigma_comparison"
      ]
    },
    {
      "page": "plot_Sigma_heatmap",
      "title": "Plot Sigma-table rows as a trait-by-trait heatmap",
      "topics": [
        "plot_Sigma_heatmap"
      ]
    },
    {
      "page": "plot_Sigma_table",
      "title": "Plot report-ready Sigma table rows",
      "topics": [
        "plot_Sigma_table"
      ]
    },
    {
      "page": "plot.gllvmTMB_multi",
      "title": "Plot a fitted multivariate gllvmTMB model",
      "topics": [
        "plot.gllvmTMB_multi"
      ]
    },
    {
      "page": "plot.gllvmTMBmesh",
      "title": "Plot a gllvmTMB SPDE mesh",
      "topics": [
        "plot.gllvmTMBmesh",
        "plot.sdmTMBmesh"
      ]
    },
    {
      "page": "plot.profile_derived",
      "title": "Plot a profile-derived LR curve",
      "topics": [
        "plot.profile_derived"
      ]
    },
    {
      "page": "plot.profile_loadings",
      "title": "Plot a profile_loadings object (LR U-shape per entry)",
      "topics": [
        "plot.profile_loadings"
      ]
    },
    {
      "page": "predict_cross_covariance",
      "title": "Predict pair-specific cross-lineage covariance",
      "topics": [
        "predict_cross_covariance"
      ]
    },
    {
      "page": "predict_missing",
      "title": "Predict the masked (missing) response cells of a gllvmTMB fit",
      "topics": [
        "predict_missing"
      ]
    },
    {
      "page": "predict.gllvmTMB_multi",
      "title": "Predict from a fitted gllvmTMB model",
      "topics": [
        "predict.gllvmTMB_multi"
      ]
    },
    {
      "page": "predictive_check",
      "title": "Fitted-model predictive checks for a multivariate 'gllvmTMB' fit",
      "topics": [
        "predictive_check"
      ]
    },
    {
      "page": "print.gllvmTMB_Sigma_phy_slope",
      "title": "Print an augmented latent-slope Sigma extraction",
      "topics": [
        "print.gllvmTMB_Sigma_phy_slope"
      ]
    },
    {
      "page": "profile_ci_total_variance",
      "title": "Profile-likelihood CI for per-trait total variance",
      "topics": [
        "profile_ci_total_variance"
      ]
    },
    {
      "page": "profile_cross_rho",
      "title": "Profile fixed cross-lineage rho values",
      "topics": [
        "profile_cross_rho"
      ]
    },
    {
      "page": "profile_cross_rho_ci",
      "title": "Profile sensitivity interval for the cross-lineage 'rho'",
      "topics": [
        "profile_cross_rho_ci"
      ]
    },
    {
      "page": "profile_phylo_signal",
      "title": "Profile-likelihood curve(s) for per-trait phylogenetic signal",
      "topics": [
        "profile_phylo_signal"
      ]
    },
    {
      "page": "profile_targets",
      "title": "List profile-ready confidence-interval targets for a fitted model",
      "topics": [
        "profile_targets"
      ]
    },
    {
      "page": "residuals.gllvmTMB_multi",
      "title": "Diagnostic residuals for a multivariate 'gllvmTMB' fit",
      "topics": [
        "residuals.gllvmTMB_multi"
      ]
    },
    {
      "page": "ridge_path",
      "title": "Sweep the loading-ridge penalty and report a stability path",
      "topics": [
        "ridge_path"
      ]
    },
    {
      "page": "rotate_loadings",
      "title": "Rotate the loadings of a fitted multivariate model",
      "topics": [
        "rotate_loadings"
      ]
    },
    {
      "page": "sanity_multi",
      "title": "Print a quick convergence and parameter sanity report",
      "topics": [
        "sanity_multi"
      ]
    },
    {
      "page": "scalar",
      "title": "One shared trait variance: 'scalar(0 + trait | g)'",
      "topics": [
        "scalar"
      ]
    },
    {
      "page": "screen_control",
      "title": "Control pre-fit response screening",
      "topics": [
        "screen_control"
      ]
    },
    {
      "page": "screen_gllvmTMB",
      "title": "Screen candidate responses before fitting a gllvmTMB model",
      "topics": [
        "screen_gllvmTMB"
      ]
    },
    {
      "page": "screen_table",
      "title": "Extract tables from a pre-fit screen",
      "topics": [
        "screen_table"
      ]
    },
    {
      "page": "simulate_site_trait",
      "title": "Simulate a functional-biogeography GLLVM dataset (sites × species × traits)",
      "topics": [
        "simulate_site_trait"
      ]
    },
    {
      "page": "simulate_unit_trait",
      "title": "Simulate a generic stacked-trait GLLVM dataset (units x observations x traits)",
      "topics": [
        "simulate_unit_trait"
      ]
    },
    {
      "page": "simulate.gllvmTMB_multi",
      "title": "Simulate new responses from a fitted gllvmTMB model",
      "topics": [
        "simulate.gllvmTMB_multi"
      ]
    },
    {
      "page": "slope_sd_ci",
      "title": "Wald confidence intervals on augmented random-slope standard deviations",
      "topics": [
        "slope_sd_ci"
      ]
    },
    {
      "page": "spatial",
      "title": "Spatial random field: lme4-bar mode-dispatch wrapper",
      "topics": [
        "spatial"
      ]
    },
    {
      "page": "spatial_dep",
      "title": "Full unstructured spatial trait covariance: 'spatial_dep(0 + trait | coords)'",
      "topics": [
        "spatial_dep"
      ]
    },
    {
      "page": "spatial_indep",
      "title": "Per-trait spatial marginal field: 'spatial_indep(0 + trait | coords)'",
      "topics": [
        "spatial_indep"
      ]
    },
    {
      "page": "spatial_latent",
      "title": "Reduced-rank spatial latent factors: 'spatial_latent(0 + trait | coords, d = K)'",
      "topics": [
        "spatial_latent"
      ]
    },
    {
      "page": "spatial_scalar",
      "title": "Deprecated alias for one shared spatial-field variance",
      "topics": [
        "spatial_scalar"
      ]
    },
    {
      "page": "spatial_unique",
      "title": "Per-trait independent spatial random fields: 'spatial_unique(0 + trait | coords)'",
      "topics": [
        "spatial_unique"
      ]
    },
    {
      "page": "standard_errors",
      "title": "Compute standard errors after fitting",
      "topics": [
        "standard_errors"
      ]
    },
    {
      "page": "suggest_lambda_constraint",
      "title": "Suggest a 'lambda_constraint' matrix for a reduced-rank fit",
      "topics": [
        "suggest_lambda_constraint"
      ]
    },
    {
      "page": "suggest_lambda_constraints",
      "title": "Compare several 'lambda_constraint' suggestions",
      "topics": [
        "suggest_lambda_constraints"
      ]
    },
    {
      "page": "tidy.gllvmTMB_multi",
      "title": "Tidy a fitted gllvmTMB model",
      "topics": [
        "tidy.gllvmTMB_multi"
      ]
    },
    {
      "page": "traits",
      "title": "Wide-format trait marker for the 'gllvmTMB()' formula LHS",
      "topics": [
        "traits"
      ]
    }
  ],
  "_pkglogo": "https://github.com/cran/gllvmTMB/raw/HEAD/man/figures/logo.png",
  "_readme": "https://github.com/cran/gllvmTMB/raw/HEAD/README.md",
  "_rundeps": [
    "assertthat",
    "BH",
    "class",
    "classInt",
    "cli",
    "DBI",
    "dplyr",
    "e1071",
    "fmesher",
    "generics",
    "glue",
    "KernSmooth",
    "lattice",
    "lifecycle",
    "magrittr",
    "Matrix",
    "pillar",
    "pkgconfig",
    "proxy",
    "R6",
    "Rcpp",
    "RcppEigen",
    "rlang",
    "s2",
    "sf",
    "sp",
    "splancs",
    "tibble",
    "tidyselect",
    "TMB",
    "units",
    "utf8",
    "vctrs",
    "withr",
    "wk"
  ],
  "_sysdeps": [
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "16-20260322-1ubuntu1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_vignettes": [
    {
      "source": "gllvmTMB.Rmd",
      "filename": "gllvmTMB.html",
      "title": "Get started with gllvmTMB",
      "engine": "knitr::rmarkdown",
      "headings": [
        "First fit: wide individual-by-trait morphology",
        "Same model, long data",
        "What if some response cells are missing?",
        "Check the fitted response distribution",
        "Read the covariance summaries first",
        "Choose a covariance source and level",
        "Then inspect loadings and scores",
        "Choose your next guide",
        "Acknowledgements"
      ],
      "created": "2026-10-28 21:45:14",
      "modified": "2026-10-28 21:45:14",
      "commits": 1
    }
  ],
  "_score": 4.173186268412274,
  "_indexed": true,
  "_nocasepkg": "gllvmtmb",
  "_universes": [
    "cran",
    "itchyshin"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.7.1",
      "date": "2026-10-28T23:40:08.000Z",
      "distro": "resolute",
      "arch": "aarch64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/d2ebb600e780cb617147f99c0407296ebc507aa425006d56c2d4618541dac8e0",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.7.1",
      "date": "2026-10-28T23:40:38.000Z",
      "distro": "resolute",
      "arch": "x86_64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/8665f098f7d96ae60a8aefeeb00c61a0f68e76d046924f910d6c61193afaadf4",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.6.1",
      "os": "linux",
      "version": "0.7.1",
      "date": "2026-10-28T23:40:01.000Z",
      "distro": "resolute",
      "arch": "aarch64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/9259826eed93a388d74d663d5fe9a0a8ad5776d66363eceb11e47ba0497be911",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.6.1",
      "os": "linux",
      "version": "0.7.1",
      "date": "2026-10-28T23:40:40.000Z",
      "distro": "resolute",
      "arch": "x86_64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/13e8d20a4e4f4082c8ac8c33c852adbdeb26f84dd8e3b213898b2a1708d43b02",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.7.1",
      "date": "2026-10-28T23:41:13.000Z",
      "arch": "emscripten",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/61bc8b53855e5d8a6faf9a287c9163b703beb3100c2dd5ebc471fa3fc75c1fa7",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.7.1",
      "date": "2026-10-28T23:41:29.000Z",
      "arch": "aarch64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/715669be89a5b7f2c3998d1b693d1ff563222a06f702da2c0fc0ab986977a7db",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.7.1",
      "date": "2026-10-28T23:39:50.000Z",
      "arch": "x86_64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/9c6ce83e9cc94a1f154b046655a70039848bc0231bd0d62ddf68e146f5b42a8b",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.6.1",
      "os": "win",
      "version": "0.7.1",
      "date": "2026-10-28T23:42:00.000Z",
      "arch": "aarch64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/aa27bf3de33b74750f595880ba6cbf7f5bcb6bd404407f8d57f971f42f1674f2",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    },
    {
      "r": "4.6.1",
      "os": "win",
      "version": "0.7.1",
      "date": "2026-10-28T23:39:28.000Z",
      "arch": "x86_64",
      "commit": "ca1db6d43584ae5bd7c51096aa21793b363c37f4",
      "fileid": "https://r2.ropensci.org/fb5232a1b0136b24cf304cc2207d6fe5fc0e8b4e2ddc80b1ead0563b6432ab66",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/40787456932"
    }
  ]
}