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  "Title": "Bayesian Treed Gaussian Process Models",
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  "Date": "2024-08-22",
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  "Description": "Bayesian nonstationary, semiparametric nonlinear\nregression and design by treed Gaussian processes (GPs) with\njumps to the limiting linear model (LLM).  Special cases also\nimplemented include Bayesian linear models, CART, treed linear\nmodels, stationary separable and isotropic GPs, and GP\nsingle-index models.  Provides 1-d and 2-d plotting functions\n(with projection and slice capabilities) and tree drawing,\ndesigned for visualization of tgp-class output.  Sensitivity\nanalysis and multi-resolution models are supported. Sequential\nexperimental design and adaptive sampling functions are also\nprovided, including ALM, ALC, and expected improvement.  The\nlatter supports derivative-free optimization of noisy black-box\nfunctions.  For details and tutorials, see Gramacy (2007)\n<doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010)\n<doi:10.18637/jss.v033.i06>.",
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      "title": "The Treed Gaussian Process Model Package",
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      "page": "btgp",
      "title": "Bayesian Nonparametric & Nonstationary Regression Models",
      "topics": [
        "bcart",
        "bgp",
        "bgpllm",
        "blm",
        "btgp",
        "btgpllm",
        "btlm"
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