{
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  "Title": "Kriging Models using the 'libKriging' Library",
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  "Maintainer": "Yann Richet <yann.richet@asnr.fr>",
  "Description": "Interface to 'libKriging' 'C++' library\n<https://github.com/libKriging> that should provide most\nstandard Kriging / Gaussian process regression features (like\nin 'DiceKriging', 'kergp' or 'RobustGaSP' packages).\n'libKriging' relies on Armadillo linear algebra library (Apache\n2 license) by Conrad Sanderson, 'lbfgsb_cpp' is a 'C++' port\naround by Pascal Have of 'lbfgsb' library (BSD-3 license) by\nCiyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales\nused for hyperparameters optimization.",
  "License": "Apache License (>= 2)",
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  "Author": "Yann Richet [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-5677-8458>), Pascal Havé [aut],\nYves Deville [aut], Conrad Sanderson [ctb], Ciyou Zhu [ctb],\nRichard Byrd [ctb], Jorge Nocedal [ctb], Jose Luis Morales\n[ctb], Mike Smith [ctb]",
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  "_exports": [
    "activation",
    "as.km",
    "beta",
    "centerX",
    "centerY",
    "copy",
    "covMat",
    "F_",
    "feature_dim",
    "fit",
    "hidden_dims",
    "is_fitted",
    "kernel",
    "KM",
    "Kriging",
    "leaveOneOut",
    "leaveOneOutFun",
    "leaveOneOutVec",
    "load",
    "load.Kriging",
    "logLikelihood",
    "logLikelihoodFun",
    "logMargPost",
    "logMargPostFun",
    "M",
    "MLPKriging",
    "normalize",
    "predict",
    "regmodel",
    "save",
    "scaleX",
    "scaleY",
    "sigma2",
    "simulate",
    "T_",
    "theta",
    "update",
    "update_simulate",
    "warp_affine",
    "warp_boxcox",
    "warp_categorical",
    "warp_knots",
    "warp_kumaraswamy",
    "warp_mlp",
    "warp_neural_mono",
    "warp_none",
    "warp_ordinal",
    "warping",
    "WarpKriging",
    "X",
    "y",
    "z"
  ],
  "_help": [
    {
      "page": "activation",
      "title": "Get activation function name",
      "topics": [
        "activation"
      ]
    },
    {
      "page": "activation.MLPKriging",
      "title": "Get activation function for an MLPKriging model",
      "topics": [
        "activation.MLPKriging"
      ]
    },
    {
      "page": "as.km",
      "title": "Coerce an Object into a 'km' Object",
      "topics": [
        "as.km"
      ]
    },
    {
      "page": "as.km.Kriging",
      "title": "Coerce a 'Kriging' object into the '\"km\"' class of the 'DiceKriging' package.",
      "topics": [
        "as.km,Kriging,Kriging-method",
        "as.km.Kriging"
      ]
    },
    {
      "page": "as.list.Kriging",
      "title": "Coerce a 'Kriging' Object into a List",
      "topics": [
        "as.list,Kriging,Kriging-method",
        "as.list.Kriging"
      ]
    },
    {
      "page": "beta",
      "title": "Get trend coefficients beta",
      "topics": [
        "beta"
      ]
    },
    {
      "page": "beta.MLPKriging",
      "title": "Get trend coefficients beta for an MLPKriging model",
      "topics": [
        "beta.MLPKriging"
      ]
    },
    {
      "page": "beta.WarpKriging",
      "title": "Get trend coefficients beta for a WarpKriging model",
      "topics": [
        "beta.WarpKriging"
      ]
    },
    {
      "page": "centerX",
      "title": "Get input centering vector",
      "topics": [
        "centerX"
      ]
    },
    {
      "page": "centerX.MLPKriging",
      "title": "Get input centering vector for an MLPKriging model",
      "topics": [
        "centerX.MLPKriging"
      ]
    },
    {
      "page": "centerX.WarpKriging",
      "title": "Get input centering vector for a WarpKriging model",
      "topics": [
        "centerX.WarpKriging"
      ]
    },
    {
      "page": "centerY",
      "title": "Get output centering value",
      "topics": [
        "centerY"
      ]
    },
    {
      "page": "centerY.MLPKriging",
      "title": "Get output centering value for an MLPKriging model",
      "topics": [
        "centerY.MLPKriging"
      ]
    },
    {
      "page": "centerY.WarpKriging",
      "title": "Get output centering value for a WarpKriging model",
      "topics": [
        "centerY.WarpKriging"
      ]
    },
    {
      "page": "classKriging",
      "title": "Shortcut to provide functions to the S3 class \"Kriging\"",
      "topics": [
        "classKriging"
      ]
    },
    {
      "page": "classMLPKriging",
      "title": "Shortcut to provide functions to the S3 class \"MLPKriging\"",
      "topics": [
        "classMLPKriging"
      ]
    },
    {
      "page": "classWarpKriging",
      "title": "Shortcut to provide functions to the S3 class \"WarpKriging\"",
      "topics": [
        "classWarpKriging"
      ]
    },
    {
      "page": "copy",
      "title": "Duplicate object.",
      "topics": [
        "copy"
      ]
    },
    {
      "page": "copy.Kriging",
      "title": "Duplicate a Kriging Model",
      "topics": [
        "copy,Kriging,Kriging-method",
        "copy.Kriging"
      ]
    },
    {
      "page": "copy.MLPKriging",
      "title": "Deep copy of MLPKriging model",
      "topics": [
        "copy.MLPKriging"
      ]
    },
    {
      "page": "copy.WarpKriging",
      "title": "Deep copy of WarpKriging model",
      "topics": [
        "copy.WarpKriging"
      ]
    },
    {
      "page": "covMat",
      "title": "covariance function",
      "topics": [
        "covMat"
      ]
    },
    {
      "page": "covMat.Kriging",
      "title": "Compute Covariance Matrix of Kriging Model",
      "topics": [
        "covMat,Kriging,Kriging-method",
        "covMat.Kriging"
      ]
    },
    {
      "page": "F_",
      "title": "Get trend matrix F",
      "topics": [
        "F_"
      ]
    },
    {
      "page": "F_.MLPKriging",
      "title": "Get trend matrix F for an MLPKriging model",
      "topics": [
        "F_.MLPKriging"
      ]
    },
    {
      "page": "F_.WarpKriging",
      "title": "Get trend matrix F for a WarpKriging model",
      "topics": [
        "F_.WarpKriging"
      ]
    },
    {
      "page": "feature_dim",
      "title": "Get feature dimensionality (d_out)",
      "topics": [
        "feature_dim"
      ]
    },
    {
      "page": "feature_dim.MLPKriging",
      "title": "Get feature dimensionality for an MLPKriging model",
      "topics": [
        "feature_dim.MLPKriging"
      ]
    },
    {
      "page": "feature_dim.WarpKriging",
      "title": "Get feature dimensionality of warped space",
      "topics": [
        "feature_dim.WarpKriging"
      ]
    },
    {
      "page": "fit",
      "title": "Fit model on data.",
      "topics": [
        "fit"
      ]
    },
    {
      "page": "fit.Kriging",
      "title": "Fit 'Kriging' object on given data.",
      "topics": [
        "fit.Kriging"
      ]
    },
    {
      "page": "fit.MLPKriging",
      "title": "Fit an MLPKriging model to data",
      "topics": [
        "fit.MLPKriging"
      ]
    },
    {
      "page": "fit.WarpKriging",
      "title": "Fit a WarpKriging model to data",
      "topics": [
        "fit.WarpKriging"
      ]
    },
    {
      "page": "hidden_dims",
      "title": "Get hidden layer sizes",
      "topics": [
        "hidden_dims"
      ]
    },
    {
      "page": "hidden_dims.MLPKriging",
      "title": "Get hidden layer sizes for an MLPKriging model",
      "topics": [
        "hidden_dims.MLPKriging"
      ]
    },
    {
      "page": "is_fitted",
      "title": "Check if the model has been fitted",
      "topics": [
        "is_fitted"
      ]
    },
    {
      "page": "is_fitted.MLPKriging",
      "title": "Check whether an MLPKriging model is fitted",
      "topics": [
        "is_fitted.MLPKriging"
      ]
    },
    {
      "page": "is_fitted.WarpKriging",
      "title": "Check whether a WarpKriging model is fitted",
      "topics": [
        "is_fitted.WarpKriging"
      ]
    },
    {
      "page": "kernel",
      "title": "Get kernel name",
      "topics": [
        "kernel"
      ]
    },
    {
      "page": "kernel.WarpKriging",
      "title": "Get kernel name",
      "topics": [
        "kernel.WarpKriging"
      ]
    },
    {
      "page": "KM",
      "title": "Create an 'KM' Object",
      "topics": [
        "KM"
      ]
    },
    {
      "page": "KM-class",
      "title": "S4 class for Kriging Models Extending the '\"km\"' Class",
      "topics": [
        "KM-class"
      ]
    },
    {
      "page": "Kriging",
      "title": "Create an object with S3 class '\"Kriging\"' using the 'libKriging' library.",
      "topics": [
        "Kriging"
      ]
    },
    {
      "page": "leaveOneOut",
      "title": "Compute Leave-One-Out",
      "topics": [
        "leaveOneOut"
      ]
    },
    {
      "page": "leaveOneOut.Kriging",
      "title": "Get leaveOneOut of Kriging Model",
      "topics": [
        "leaveOneOut,Kriging,Kriging-method",
        "leaveOneOut.Kriging"
      ]
    },
    {
      "page": "leaveOneOutFun",
      "title": "Leave-One-Out function",
      "topics": [
        "leaveOneOutFun"
      ]
    },
    {
      "page": "leaveOneOutFun.Kriging",
      "title": "Compute Leave-One-Out (LOO) error for an object with S3 class '\"Kriging\"' representing a kriging model.",
      "topics": [
        "leaveOneOutFun,Kriging,Kriging-method",
        "leaveOneOutFun.Kriging"
      ]
    },
    {
      "page": "leaveOneOutVec",
      "title": "Leave-One-Out vector",
      "topics": [
        "leaveOneOutVec"
      ]
    },
    {
      "page": "leaveOneOutVec.Kriging",
      "title": "Compute Leave-One-Out (LOO) vector error for an object with S3 class '\"Kriging\"' representing a kriging model.",
      "topics": [
        "leaveOneOutVec,Kriging,Kriging-method",
        "leaveOneOutVec.Kriging"
      ]
    },
    {
      "page": "load",
      "title": "Load any Kriging Model from a file storage. Back to base::load if not a Kriging object.",
      "topics": [
        "load"
      ]
    },
    {
      "page": "load.Kriging",
      "title": "Load a Kriging Model from a file storage",
      "topics": [
        "load.Kriging"
      ]
    },
    {
      "page": "load.MLPKriging",
      "title": "Load an MLPKriging model from file",
      "topics": [
        "load.MLPKriging"
      ]
    },
    {
      "page": "load.WarpKriging",
      "title": "Load a WarpKriging model from file",
      "topics": [
        "load.WarpKriging"
      ]
    },
    {
      "page": "logLikelihood",
      "title": "Compute Log-Likelihood",
      "topics": [
        "logLikelihood"
      ]
    },
    {
      "page": "logLikelihood.Kriging",
      "title": "Get Log-Likelihood of Kriging Model",
      "topics": [
        "logLikelihood,Kriging,Kriging-method",
        "logLikelihood.Kriging"
      ]
    },
    {
      "page": "logLikelihood.WarpKriging",
      "title": "Log-likelihood of the fitted model",
      "topics": [
        "logLikelihood.WarpKriging"
      ]
    },
    {
      "page": "logLikelihoodFun",
      "title": "Log-Likelihood function",
      "topics": [
        "logLikelihoodFun"
      ]
    },
    {
      "page": "logLikelihoodFun.Kriging",
      "title": "Compute Log-Likelihood of Kriging Model",
      "topics": [
        "logLikelihoodFun,Kriging,Kriging-method",
        "logLikelihoodFun.Kriging"
      ]
    },
    {
      "page": "logLikelihoodFun.MLPKriging",
      "title": "Evaluate log-likelihood at given GP theta",
      "topics": [
        "logLikelihoodFun.MLPKriging"
      ]
    },
    {
      "page": "logLikelihoodFun.WarpKriging",
      "title": "Evaluate log-likelihood at given theta",
      "topics": [
        "logLikelihoodFun.WarpKriging"
      ]
    },
    {
      "page": "logMargPost",
      "title": "Compute log-Marginal Posterior",
      "topics": [
        "logMargPost"
      ]
    },
    {
      "page": "logMargPost.Kriging",
      "title": "Get logMargPost of Kriging Model",
      "topics": [
        "logMargPost,Kriging,Kriging-method",
        "logMargPost.Kriging"
      ]
    },
    {
      "page": "logMargPostFun",
      "title": "log-Marginal Posterior function",
      "topics": [
        "logMargPostFun"
      ]
    },
    {
      "page": "logMargPostFun.Kriging",
      "title": "Compute the log-marginal posterior of a kriging model, using the prior XXXY.",
      "topics": [
        "logMargPostFun,Kriging,Kriging-method",
        "logMargPostFun.Kriging"
      ]
    },
    {
      "page": "M",
      "title": "Get whitened trend matrix M",
      "topics": [
        "M"
      ]
    },
    {
      "page": "M.MLPKriging",
      "title": "Get whitened trend matrix M for an MLPKriging model",
      "topics": [
        "M.MLPKriging"
      ]
    },
    {
      "page": "M.WarpKriging",
      "title": "Get whitened trend matrix M for a WarpKriging model",
      "topics": [
        "M.WarpKriging"
      ]
    },
    {
      "page": "MLPKriging",
      "title": "Create an MLPKriging model (Deep Kernel Learning)",
      "topics": [
        "MLPKriging"
      ]
    },
    {
      "page": "NoiseKM",
      "title": "Create a KM object with heteroscedastic noise (deprecated)",
      "topics": [
        "NoiseKM"
      ]
    },
    {
      "page": "normalize",
      "title": "Get normalize flag",
      "topics": [
        "normalize"
      ]
    },
    {
      "page": "normalize.MLPKriging",
      "title": "Get normalize flag for an MLPKriging model",
      "topics": [
        "normalize.MLPKriging"
      ]
    },
    {
      "page": "normalize.WarpKriging",
      "title": "Get normalize flag for a WarpKriging model",
      "topics": [
        "normalize.WarpKriging"
      ]
    },
    {
      "page": "NuggetKM",
      "title": "Create a KM object with nugget effect (deprecated)",
      "topics": [
        "NuggetKM"
      ]
    },
    {
      "page": "predict-KM-method",
      "title": "Prediction Method for a 'KM' Object",
      "topics": [
        "predict,KM-method"
      ]
    },
    {
      "page": "predict.Kriging",
      "title": "Predict from a 'Kriging' object.",
      "topics": [
        "predict.Kriging"
      ]
    },
    {
      "page": "predict.MLPKriging",
      "title": "Predict with an MLPKriging model",
      "topics": [
        "predict.MLPKriging"
      ]
    },
    {
      "page": "predict.WarpKriging",
      "title": "Predict with a WarpKriging model",
      "topics": [
        "predict.WarpKriging"
      ]
    },
    {
      "page": "print.Kriging",
      "title": "Print the content of a 'Kriging' object.",
      "topics": [
        "print.Kriging"
      ]
    },
    {
      "page": "regmodel",
      "title": "Get regression model type",
      "topics": [
        "regmodel"
      ]
    },
    {
      "page": "regmodel.MLPKriging",
      "title": "Get regression model type for an MLPKriging model",
      "topics": [
        "regmodel.MLPKriging"
      ]
    },
    {
      "page": "regmodel.WarpKriging",
      "title": "Get regression model type for a WarpKriging model",
      "topics": [
        "regmodel.WarpKriging"
      ]
    },
    {
      "page": "save",
      "title": "Save a Kriging Model inside a file. Back to base::save if argument is not a Kriging object.",
      "topics": [
        "save"
      ]
    },
    {
      "page": "save.Kriging",
      "title": "Save a Kriging Model to a file storage",
      "topics": [
        "save,Kriging,Kriging-method",
        "save.Kriging"
      ]
    },
    {
      "page": "save.MLPKriging",
      "title": "Save an MLPKriging model to file",
      "topics": [
        "save.MLPKriging"
      ]
    },
    {
      "page": "save.WarpKriging",
      "title": "Save a WarpKriging model to file",
      "topics": [
        "save.WarpKriging"
      ]
    },
    {
      "page": "scaleX",
      "title": "Get input scaling vector",
      "topics": [
        "scaleX"
      ]
    },
    {
      "page": "scaleX.MLPKriging",
      "title": "Get input scaling vector for an MLPKriging model",
      "topics": [
        "scaleX.MLPKriging"
      ]
    },
    {
      "page": "scaleX.WarpKriging",
      "title": "Get input scaling vector for a WarpKriging model",
      "topics": [
        "scaleX.WarpKriging"
      ]
    },
    {
      "page": "scaleY",
      "title": "Get output scaling value",
      "topics": [
        "scaleY"
      ]
    },
    {
      "page": "scaleY.MLPKriging",
      "title": "Get output scaling value for an MLPKriging model",
      "topics": [
        "scaleY.MLPKriging"
      ]
    },
    {
      "page": "scaleY.WarpKriging",
      "title": "Get output scaling value for a WarpKriging model",
      "topics": [
        "scaleY.WarpKriging"
      ]
    },
    {
      "page": "sigma2",
      "title": "Get process variance",
      "topics": [
        "sigma2"
      ]
    },
    {
      "page": "sigma2.WarpKriging",
      "title": "Get process variance (concentrated MLE)",
      "topics": [
        "sigma2.WarpKriging"
      ]
    },
    {
      "page": "simulate-KM-method",
      "title": "Simulation from a 'KM' Object",
      "topics": [
        "simulate,KM-method"
      ]
    },
    {
      "page": "simulate.Kriging",
      "title": "Simulation from a 'Kriging' model object.",
      "topics": [
        "simulate.Kriging"
      ]
    },
    {
      "page": "simulate.MLPKriging",
      "title": "Simulate from an MLPKriging model",
      "topics": [
        "simulate.MLPKriging"
      ]
    },
    {
      "page": "simulate.WarpKriging",
      "title": "Simulate from a WarpKriging model",
      "topics": [
        "simulate.WarpKriging"
      ]
    },
    {
      "page": "T_",
      "title": "Get Cholesky factor T",
      "topics": [
        "T_"
      ]
    },
    {
      "page": "T_.MLPKriging",
      "title": "Get Cholesky factor T for an MLPKriging model",
      "topics": [
        "T_.MLPKriging"
      ]
    },
    {
      "page": "T_.WarpKriging",
      "title": "Get Cholesky factor T for a WarpKriging model",
      "topics": [
        "T_.WarpKriging"
      ]
    },
    {
      "page": "theta",
      "title": "Get GP range parameters",
      "topics": [
        "theta"
      ]
    },
    {
      "page": "theta.WarpKriging",
      "title": "Get GP range parameters",
      "topics": [
        "theta.WarpKriging"
      ]
    },
    {
      "page": "update_simulate",
      "title": "Update simulation of model on data.",
      "topics": [
        "update_simulate"
      ]
    },
    {
      "page": "update_simulate.Kriging",
      "title": "Update previous simulation of a 'Kriging' model object.",
      "topics": [
        "update_simulate.Kriging"
      ]
    },
    {
      "page": "update_simulate.MLPKriging",
      "title": "Update simulated paths with new observations (FOXY algorithm)",
      "topics": [
        "update_simulate.MLPKriging"
      ]
    },
    {
      "page": "update_simulate.WarpKriging",
      "title": "Update simulated paths with new observations (FOXY algorithm)",
      "topics": [
        "update_simulate.WarpKriging"
      ]
    },
    {
      "page": "update-KM-method",
      "title": "Update a 'KM' Object with New Points",
      "topics": [
        "update,KM-method"
      ]
    },
    {
      "page": "update.Kriging",
      "title": "Update a 'Kriging' model object with new points",
      "topics": [
        "update.Kriging"
      ]
    },
    {
      "page": "update.MLPKriging",
      "title": "Update an MLPKriging model with new observations",
      "topics": [
        "update.MLPKriging"
      ]
    },
    {
      "page": "update.WarpKriging",
      "title": "Update a WarpKriging model with new observations",
      "topics": [
        "update.WarpKriging"
      ]
    },
    {
      "page": "warp_affine",
      "title": "Affine warping: w(x) = a*x + b",
      "topics": [
        "warp_affine"
      ]
    },
    {
      "page": "warp_boxcox",
      "title": "Box-Cox warping",
      "topics": [
        "warp_boxcox"
      ]
    },
    {
      "page": "warp_categorical",
      "title": "Categorical embedding",
      "topics": [
        "warp_categorical"
      ]
    },
    {
      "page": "warp_knots",
      "title": "Piecewise-linear monotone warping with knots (Xiong et al. 2007)",
      "topics": [
        "warp_knots"
      ]
    },
    {
      "page": "warp_kumaraswamy",
      "title": "Kumaraswamy CDF warping on [0,1]",
      "topics": [
        "warp_kumaraswamy"
      ]
    },
    {
      "page": "warp_mlp",
      "title": "Per-variable MLP warping (unconstrained, multi-dim output)",
      "topics": [
        "warp_mlp"
      ]
    },
    {
      "page": "warp_neural_mono",
      "title": "Monotone neural network warping",
      "topics": [
        "warp_neural_mono"
      ]
    },
    {
      "page": "warp_none",
      "title": "No warping (identity)",
      "topics": [
        "warp_none"
      ]
    },
    {
      "page": "warp_ordinal",
      "title": "Ordinal warping (learned ordered positions)",
      "topics": [
        "warp_ordinal"
      ]
    },
    {
      "page": "warping",
      "title": "Get warping specifications as strings",
      "topics": [
        "warping"
      ]
    },
    {
      "page": "warping.WarpKriging",
      "title": "Get warping specification for a WarpKriging model",
      "topics": [
        "warping.WarpKriging"
      ]
    },
    {
      "page": "WarpKriging",
      "title": "Create a WarpKriging model",
      "topics": [
        "WarpKriging"
      ]
    },
    {
      "page": "X",
      "title": "Get training input matrix",
      "topics": [
        "X"
      ]
    },
    {
      "page": "X.MLPKriging",
      "title": "Get training input matrix",
      "topics": [
        "X.MLPKriging"
      ]
    },
    {
      "page": "y",
      "title": "Get training output vector",
      "topics": [
        "y"
      ]
    },
    {
      "page": "y.MLPKriging",
      "title": "Get training output vector",
      "topics": [
        "y.MLPKriging"
      ]
    },
    {
      "page": "z",
      "title": "Get whitened residuals z",
      "topics": [
        "z"
      ]
    },
    {
      "page": "z.MLPKriging",
      "title": "Get whitened residuals z for an MLPKriging model",
      "topics": [
        "z.MLPKriging"
      ]
    },
    {
      "page": "z.WarpKriging",
      "title": "Get whitened residuals z for a WarpKriging model",
      "topics": [
        "z.WarpKriging"
      ]
    }
  ],
  "_readme": "https://github.com/cran/rlibkriging/raw/HEAD/README.md",
  "_rundeps": [
    "DiceKriging",
    "Rcpp",
    "RcppArmadillo"
  ],
  "_sysdeps": [
    {
      "shlib": "libopenblasp-r0",
      "package": "libopenblas0-pthread",
      "headers": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    },
    {
      "shlib": "libarpack",
      "package": "libarpack2t64",
      "headers": "libarpack2-dev",
      "source": "arpack",
      "version": "3.9.1-1.1build2",
      "name": "arpack",
      "homepage": "https://github.com/opencollab/arpack-ng",
      "description": "Fortran77 subroutines to solve large scale eigenvalue problems"
    },
    {
      "shlib": "libgomp",
      "package": "libgomp1",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "openmp",
      "homepage": "http://gcc.gnu.org/",
      "description": "GCC OpenMP (GOMP) support library"
    },
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_score": 3.4807253789884873,
  "_indexed": false,
  "_nocasepkg": "rlibkriging",
  "_universes": [
    "cran"
  ],
  "_indexurl": "https://yannrichet-asnr.r-universe.dev/rlibkriging",
  "_binaries": [
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.0-0",
      "date": "2026-06-12T10:54:24.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "2b7b399730904fcbd45abf26ca1b4ae391f85425",
      "fileid": "0cc38991e7ef1d4a41ab8b3270a8ff477e958c1a0f56bf8d1d2557fdd14a2dcb",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/27411040098"
    }
  ]
}