{
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  "Package": "underdisp",
  "Type": "Package",
  "Title": "Diagnostics and Models for Underdispersed Count Data",
  "Version": "0.1.2",
  "Authors@R": "person(\"Benjamin E.\", \"Bagozzi\", email = \"bagozzib@udel.edu\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-6233-6453\"))",
  "Description": "Tools for detecting and modeling underdispersion in count\ndata (conditional variance below the conditional mean), the\ncase the Poisson and negative binomial defaults cannot\nrepresent. Provides a screening diagnostic that benchmarks\nat-risk dispersion against a zero-truncated Poisson,\nregression-adjusted tests of equidispersion, and a dispersion\nprofile that compares the variance-to-mean curves of competing\nfamilies against the data; the continuous parameter binomial\n(CPB) and generalized event count (Katz) regressions with\nzero-truncated, hurdle, and zero-inflated forms and\nhigh-dimensional fixed effects with a split-panel jackknife\nbias correction; matched Poisson, negative binomial,\nCOM-Poisson (rate- and mean-parameterized), generalized\nPoisson, gamma-count, and double Poisson regressions through\nthe same interface, with frequency weights, offsets, and\nanalytic, robust, and cluster-robust standard errors; bootstrap\nand profile-likelihood inference; proper scoring rules,\nrootograms, PIT histograms, and simulation methods; and\nquantities of interest including predicted distributions, the\nimplied ceiling, rate ratios, and first differences with an\nextensive/intensive decomposition. The likelihoods are\nimplemented in C++.",
  "License": "GPL-3",
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  "BugReports": "https://github.com/bagozzib/underdisp/issues",
  "Config/testthat/edition": "3",
  "Repository": "https://bagozzib.r-universe.dev",
  "Date/Publication": "2026-09-30 19:18:01 UTC",
  "RemoteUrl": "https://github.com/bagozzib/underdisp",
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  "Packaged": {
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  "Author": "Benjamin E. Bagozzi [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-6233-6453>)",
  "Maintainer": "Benjamin E. Bagozzi <bagozzib@udel.edu>",
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  "_created": "2026-10-01T00:22:31.000Z",
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    "author": "bagozzib <bagozzib@udel.edu>",
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  "_topics": [
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  "_exports": [
    "alpha_confint",
    "calibrate_alpha",
    "compare_dispersion",
    "compare_models",
    "count_reg",
    "cpb",
    "cpb_fe",
    "cv_score",
    "dcompois",
    "dcpb",
    "ddoublepois",
    "dgammacount",
    "dgec",
    "dgenpois",
    "dispersion_profile",
    "dispersion_test",
    "first_difference",
    "gec",
    "gec_fe",
    "hurdle_count",
    "hurdle_cpb",
    "hurdle_gec",
    "implied_ceiling",
    "irr",
    "mundlak",
    "pcompois",
    "pcpb",
    "pdoublepois",
    "pgammacount",
    "pgec",
    "pgenpois",
    "pit_hist",
    "qcompois",
    "qcpb",
    "qdoublepois",
    "qgammacount",
    "qgec",
    "qgenpois",
    "rcompois",
    "rcpb",
    "rdoublepois",
    "rgammacount",
    "rgec",
    "rgenpois",
    "rhurdle_cpb",
    "rootogram",
    "rzicpb",
    "score",
    "ud_screen",
    "zi_count",
    "zi_cpb",
    "zi_gec",
    "zi_test"
  ],
  "_datasets": [
    {
      "name": "peacekeeping",
      "title": "UN peacekeeping contributions, state-years",
      "object": "peacekeeping",
      "class": [
        "data.frame"
      ],
      "fields": [
        "iso3",
        "year",
        "contributions",
        "democracy",
        "lgdppc",
        "lpop",
        "milper",
        "majorpower",
        "region"
      ],
      "rows": 4448,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "alpha_confint",
      "title": "Profile-likelihood interval for the dispersion parameter alpha",
      "topics": [
        "alpha_confint"
      ]
    },
    {
      "page": "augment.cpb",
      "title": "Augment data with CPB fitted values (broom method)",
      "topics": [
        "augment.cpb"
      ]
    },
    {
      "page": "calibrate_alpha",
      "title": "Calibrate the interval for the CPB dispersion parameter",
      "topics": [
        "calibrate_alpha",
        "calibrate_alpha.cpb",
        "calibrate_alpha.default",
        "calibrate_alpha.hurdle_cpb"
      ]
    },
    {
      "page": "compare_dispersion",
      "title": "Compare count-model dispersion across the model family",
      "topics": [
        "compare_dispersion"
      ]
    },
    {
      "page": "compare_models",
      "title": "Compare fitted underdispersed-count models",
      "topics": [
        "compare_models"
      ]
    },
    {
      "page": "compois-distribution",
      "title": "Conway-Maxwell-Poisson distribution functions",
      "topics": [
        "compois-distribution",
        "dcompois",
        "pcompois",
        "qcompois",
        "rcompois"
      ]
    },
    {
      "page": "confint.cpb",
      "title": "Confidence intervals for a CPB fit",
      "topics": [
        "confint.cpb"
      ]
    },
    {
      "page": "confint.underdisp",
      "title": "Confidence intervals for every model class",
      "topics": [
        "confint.count_reg",
        "confint.cpb_fe",
        "confint.gec",
        "confint.hurdle_count",
        "confint.hurdle_cpb",
        "confint.hurdle_gec",
        "confint.underdisp",
        "confint.zi_count",
        "confint.zi_cpb",
        "confint.zi_gec"
      ]
    },
    {
      "page": "count_reg",
      "title": "Matched count regressions: Poisson, negative binomial, COM-Poisson, generalized Poisson, gamma-count, double Poisson",
      "topics": [
        "count_reg"
      ]
    },
    {
      "page": "cpb",
      "title": "Fit a Continuous Parameter Binomial (CPB) regression",
      "topics": [
        "cpb"
      ]
    },
    {
      "page": "cpb_fe",
      "title": "CPB regression with high-dimensional unit fixed effects",
      "topics": [
        "cpb_fe"
      ]
    },
    {
      "page": "cpb-distribution",
      "title": "Continuous parameter binomial distribution functions",
      "topics": [
        "cpb-distribution",
        "dcpb",
        "pcpb",
        "qcpb"
      ]
    },
    {
      "page": "cv_score",
      "title": "Cross-validated proper scores for a count model",
      "topics": [
        "cv_score"
      ]
    },
    {
      "page": "dispersion_profile",
      "title": "Dispersion profile: variance-to-mean ratio against the fitted mean",
      "topics": [
        "dispersion_profile",
        "plot.dispersion_profile"
      ]
    },
    {
      "page": "dispersion_test",
      "title": "Regression-adjusted test of equidispersion",
      "topics": [
        "dispersion_test"
      ]
    },
    {
      "page": "doublepois-distribution",
      "title": "Double Poisson distribution functions",
      "topics": [
        "ddoublepois",
        "doublepois-distribution",
        "pdoublepois",
        "qdoublepois",
        "rdoublepois"
      ]
    },
    {
      "page": "first_difference",
      "title": "First difference for a CPB fit",
      "topics": [
        "first_difference",
        "first_difference.cpb"
      ]
    },
    {
      "page": "first_difference.count",
      "title": "First differences for the matched count families",
      "topics": [
        "first_difference.count",
        "first_difference.count_reg",
        "first_difference.cpb_fe",
        "first_difference.gec",
        "first_difference.gec_fe",
        "first_difference.hurdle_count",
        "first_difference.hurdle_gec",
        "first_difference.zi_count",
        "first_difference.zi_gec"
      ]
    },
    {
      "page": "first_difference.hurdle_cpb",
      "title": "Extensive/intensive first-difference decomposition for a hurdle- or ZI-CPB",
      "topics": [
        "first_difference.hurdle_cpb",
        "first_difference.zi_cpb"
      ]
    },
    {
      "page": "fitted.underdisp",
      "title": "Fitted means for the two-part and fixed-effects classes",
      "topics": [
        "fitted.cpb_fe",
        "fitted.hurdle_count",
        "fitted.hurdle_cpb",
        "fitted.hurdle_gec",
        "fitted.underdisp",
        "fitted.zi_count",
        "fitted.zi_cpb",
        "fitted.zi_gec"
      ]
    },
    {
      "page": "gammacount-distribution",
      "title": "Gamma-count distribution functions",
      "topics": [
        "dgammacount",
        "gammacount-distribution",
        "pgammacount",
        "qgammacount",
        "rgammacount"
      ]
    },
    {
      "page": "gec",
      "title": "Generalized event count (Katz-family) regression",
      "topics": [
        "gec"
      ]
    },
    {
      "page": "gec_fe",
      "title": "GEC (Katz-family) regression with high-dimensional unit fixed effects",
      "topics": [
        "gec_fe"
      ]
    },
    {
      "page": "gec-distribution",
      "title": "Generalized event count (Katz) distribution functions",
      "topics": [
        "dgec",
        "gec-distribution",
        "pgec",
        "qgec",
        "rgec"
      ]
    },
    {
      "page": "genpois-distribution",
      "title": "Generalized Poisson distribution functions",
      "topics": [
        "dgenpois",
        "genpois-distribution",
        "pgenpois",
        "qgenpois",
        "rgenpois"
      ]
    },
    {
      "page": "glance.cpb",
      "title": "Glance at a CPB fit (broom method)",
      "topics": [
        "glance.count_reg",
        "glance.cpb",
        "glance.cpb_fe",
        "glance.gec",
        "glance.hurdle_count",
        "glance.hurdle_cpb",
        "glance.hurdle_gec",
        "glance.zi_count",
        "glance.zi_cpb",
        "glance.zi_gec"
      ]
    },
    {
      "page": "hurdle_count",
      "title": "Hurdle count regression for the matched count families",
      "topics": [
        "hurdle_count"
      ]
    },
    {
      "page": "hurdle_cpb",
      "title": "Hurdle continuous parameter binomial regression",
      "topics": [
        "hurdle_cpb"
      ]
    },
    {
      "page": "hurdle_gec",
      "title": "Hurdle GEC (Katz-family) regression",
      "topics": [
        "hurdle_gec"
      ]
    },
    {
      "page": "implied_ceiling",
      "title": "Implied ceiling with a profile-likelihood interval",
      "topics": [
        "implied_ceiling",
        "implied_ceiling.cpb",
        "implied_ceiling.cpb_fe"
      ]
    },
    {
      "page": "irr",
      "title": "Incidence rate ratios for a CPB fit",
      "topics": [
        "irr",
        "irr.cpb"
      ]
    },
    {
      "page": "irr.count",
      "title": "Rate and odds ratios for the matched count families",
      "topics": [
        "irr.count",
        "irr.count_reg",
        "irr.cpb_fe",
        "irr.gec",
        "irr.gec_fe",
        "irr.hurdle_count",
        "irr.hurdle_gec",
        "irr.zi_count",
        "irr.zi_gec"
      ]
    },
    {
      "page": "mundlak",
      "title": "Mundlak (correlated random effects) device",
      "topics": [
        "mundlak"
      ]
    },
    {
      "page": "peacekeeping",
      "title": "UN peacekeeping contributions, state-years",
      "topics": [
        "peacekeeping"
      ]
    },
    {
      "page": "pit_hist",
      "title": "Non-randomized PIT histogram for a fitted count model",
      "topics": [
        "pit_hist"
      ]
    },
    {
      "page": "predict.count_reg",
      "title": "Predictions from a matched count-family fit",
      "topics": [
        "predict.count_reg"
      ]
    },
    {
      "page": "predict.cpb",
      "title": "Predictions from a CPB fit",
      "topics": [
        "predict.cpb"
      ]
    },
    {
      "page": "predict.cpb_fe",
      "title": "Predictions from a fixed-effects CPB fit",
      "topics": [
        "predict.cpb_fe"
      ]
    },
    {
      "page": "predict.gec",
      "title": "Predictions from a generalized event count fit",
      "topics": [
        "predict.gec"
      ]
    },
    {
      "page": "predict.hurdle_count",
      "title": "Predict from a hurdle Poisson/NB fit",
      "topics": [
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      "title": "Detecting and Modeling Underdispersed Counts",
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      "headings": [
        "Simulating an underdispersed count",
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