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  "Title": "Root Mean Square Curvature Calculation",
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  "Description": "Calculates the RMS intrinsic and parameter-effects\ncurvatures of a nonlinear regression model. The curvatures are\nglobal measures of assessing whether a model/data set\ncombination is close-to-linear or not. See Bates and Watts\n(1980) <doi:10.1002/9780470316757> and Ratkowsky and Reddy\n(2017) <doi:10.1093/aesa/saw098> for details.",
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      "page": "IPEC-package",
      "title": "Root Mean Square Curvature Calculation",
      "topics": [
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        "IPEC"
      ]
    },
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      "page": "aic",
      "title": "Akaike Information Criterion (AIC) Calculation Function",
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      ]
    },
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      "page": "biasIPEC",
      "title": "Bias Calculation Function",
      "topics": [
        "biasIPEC"
      ]
    },
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      "title": "Bayesian Information Criterion (BIC) Calculation Function",
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      ]
    },
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      "title": "Bootstrap Function for Nonlinear Regression",
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      ]
    },
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      "title": "Wald Confidence Curves and the Likelihood Confidence Curves",
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    },
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