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  "Title": "Single-Index Mixture Cure Models",
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  "Description": "Single-index mixture cure models allow estimating the\nprobability of cure and the latency depending on a vector (or\nfunctional) covariate, avoiding the curse of dimensionality.\nThe vector of parameters that defines the model can be\nestimated by maximum likelihood. A nonparametric estimator for\nthe conditional density of the susceptible population is\nprovided. For more details, see Piñeiro-Lamas (2024)\n(<https://ruc.udc.es/dspace/handle/2183/37035>). Funding: This\nwork, integrated into the framework of PERTE for Vanguard\nHealth, has been co-financed by the Spanish Ministry of\nScience, Innovation and Universities with funds from the\nEuropean Union NextGenerationEU, from the Recovery,\nTransformation and Resilience Plan (PRTR-C17.I1) and from the\nAutonomous Community of Galicia within the framework of the\nBiotechnology Plan Applied to Health.",
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  "Author": "Beatriz Piñeiro-Lamas [aut, cre]\n(<https://orcid.org/0000-0003-0673-5377>), Ana López-Cheda\n[aut], Ricardo Cao [aut]",
  "Maintainer": "Beatriz Piñeiro-Lamas <b.pineiro.lamas@udc.es>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-04-21 21:20:02 UTC",
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