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  "Title": "Bayesian Inference with Laplace Approximations and P-Splines",
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  "Authors@R": "c(person(\"Oswaldo\",\"Gressani\", email=\"oswaldo_gressani@hotmail.fr\",\nrole=c(\"aut\",\"cre\"), comment = \"Author\"),\nperson(\"Philippe\", \"Lambert\", email=\"p.lambert@uliege.be\",\nrole=c(\"aut\", \"ths\"), comment = \"Co-author and thesis advisor\"))",
  "Maintainer": "Oswaldo Gressani <oswaldo_gressani@hotmail.fr>",
  "Description": "Laplace approximations and penalized B-splines are\ncombined for fast Bayesian inference in latent Gaussian models.\nThe routines can be used to fit survival models, especially\nproportional hazards and promotion time cure models (Gressani,\nO. and Lambert, P. (2018) <doi:10.1016/j.csda.2018.02.007>).\nThe Laplace-P-spline methodology can also be implemented for\ninference in (generalized) additive models (Gressani, O. and\nLambert, P. (2021) <doi:10.1016/j.csda.2020.107088>). See the\nassociated website for more information and examples.",
  "URL": "<https://github.com/oswaldogressani/blapsr>",
  "License": "GPL-3",
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  "Repository": "https://oswaldogressani.r-universe.dev",
  "Date/Publication": "2025-09-01 14:09:15 UTC",
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    "gamlps",
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    "penaltyplot",
    "simcuredata",
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    "st"
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        "children",
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      "title": "Bayesian additive partial linear modeling with Laplace-P-splines.",
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      ]
    },
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      "topics": [
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    {
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      "topics": [
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      "topics": [
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      ]
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      "title": "Survival data of male laryngeal cancer patients.",
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      "topics": [
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      "title": "Plot the approximate posterior distribution of the penalty vector.",
      "topics": [
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      ]
    },
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      "topics": [
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    },
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