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  "Title": "Hybrid Machine Learning and Random-Utility Workflow for Latent\nClass Multinomial Logit Model Specification",
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  "Authors@R": "person(\"Oliver\", \"Frings\",\nemail = \"oliver.frings@ik.me\",\nrole = c(\"aut\", \"cre\"))",
  "Author": "Oliver Frings [aut, cre]",
  "Maintainer": "Oliver Frings <oliver.frings@ik.me>",
  "Description": "Implements the three-step workflow of Frings (2026,\nworking paper) for specifying latent class multinomial logit\n(LCMNL) models. The maximum-likelihood multi-start is\ninitialised from six clusterings of respondents'\nrevealed-preference signatures (k-means, Gaussian mixture,\nhierarchical clustering with Ward, complete and average\nlinkage, and partitioning around medoids). LCMNL models are\nestimated across a user-specified range of class counts, and a\nmixed multinomial logit (MMNL) benchmark, estimated with\n'apollo', is reported alongside BIC, AIC, ICL and a\nclassification-entropy diagnostic. For large samples the\nclustering starts are computed on a capped respondent\nsubsample, and all starts are screened at a loose optimiser\ntolerance before the best is refined. Accepts long- or\nwide-format discrete-choice data with optional availability\ncolumns.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/o-frings/klue",
  "BugReports": "https://github.com/o-frings/klue/issues",
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  "Repository": "https://o-frings.r-universe.dev",
  "Date/Publication": "2026-10-26 19:25:39 UTC",
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    "message": "Start-method divergence: fit the six clustering starts separately on the H1 conditions\n\ndev/run_start_method_divergence.R fits each of the six clustering starts at full precision on the 36 H1 conditions under both designs (same conditions, seeds and designs as the H1 test) and checks the best of six against the stored multistart log-likelihood (equal in all 72). Output: per-method log-likelihoods, and a summary of agreement, spread and per-method success by design factor. Listed in README_REPRODUCE.md.\n\nCo-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>\n",
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    "klue_design",
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    "klue_draw_betas",
    "klue_fieller",
    "klue_lcmnl",
    "klue_lincom",
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    "klue_mmnl",
    "klue_mmnl_corr",
    "klue_mmnl_defaults",
    "klue_nlcom",
    "klue_par",
    "klue_predict",
    "klue_refit",
    "klue_simulate",
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    "klue_starts",
    "klue_tost",
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      "title": "Remove Apollo's global objects",
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      "title": "Direct-MLE LCMNL (MNL when C = 1)",
      "topics": [
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    },
    {
      "page": "estimate_lcmnl_cov",
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      "topics": [
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    },
    {
      "page": "estimate_lcmnl_em",
      "title": "EM estimator for the same LCMNL likelihood",
      "topics": [
        "estimate_lcmnl_em"
      ]
    },
    {
      "page": "get_all_starts",
      "title": "All clustering-based starting values",
      "topics": [
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      ]
    },
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      "title": "Starting values by perturbing the pooled MNL",
      "topics": [
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    },
    {
      "page": "get_random_partition_starts",
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      "topics": [
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    },
    {
      "page": "klue",
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      "topics": [
        "klue"
      ]
    },
    {
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    },
    {
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      "topics": [
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    {
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      "topics": [
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    },
    {
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    },
    {
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