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  "Package": "mcp",
  "Title": "Regression with Multiple Change Points",
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  "Date": "2026-10-25",
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  "Description": "Flexible and informed regression with Multiple Change\nPoints. 'mcp' can infer change points in means, variances,\nautocorrelation structure, and any combination of these, as\nwell as the parameters of the segments in between. All\nparameters are estimated with uncertainty and posterior\npredictive intervals are supported - also near the change\npoints. 'mcp' supports hypothesis testing via Savage-Dickey\ndensity ratio, posterior contrasts, and PSIS-LOO model\ncomparison. The 'mcp' framework is introduced in Lindeløv\n(2020) <doi:10.31219/osf.io/fzqxv>.",
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    "criterion",
    "fixef",
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    "hypothesis",
    "interpolate_newdata",
    "is_mcpfit",
    "is.mcpfit",
    "log_lik",
    "loo",
    "loo_compare",
    "mcp",
    "mcp_columns",
    "mcp_example",
    "mcp_example_data",
    "mcp_pars",
    "nchains",
    "ndraws",
    "negbinomial",
    "niterations",
    "phi",
    "plot_dpar",
    "plot_pars",
    "posterior_epred",
    "posterior_linpred",
    "posterior_predict",
    "pp_check",
    "prior_summary",
    "ranef",
    "sd_to_prec",
    "variables",
    "waic"
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      "title": "Pre-fitted example mcp model",
      "object": "demo_fit",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
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    {
      "page": "mcp-package",
      "title": "mcp: Regression with Multiple Change Points",
      "topics": [
        "mcp-package"
      ]
    },
    {
      "page": "as_draws.mcpfit",
      "title": "Extract MCMC Draws from 'mcpfit' Objects",
      "topics": [
        "as.array.mcpfit",
        "as.data.frame.mcpfit",
        "as.matrix.mcpfit",
        "as.mcmc.mcpfit",
        "as_draws",
        "as_draws.mcpfit",
        "as_draws_array",
        "as_draws_array.mcpfit",
        "as_draws_df",
        "as_draws_df.mcpfit",
        "as_draws_matrix",
        "as_draws_matrix.mcpfit",
        "as_draws_rvars",
        "as_draws_rvars.mcpfit",
        "tidy_draws.mcpfit"
      ]
    },
    {
      "page": "bernoulli",
      "title": "Bernoulli Family for mcp",
      "topics": [
        "bernoulli"
      ]
    },
    {
      "page": "demo_fit",
      "title": "Pre-fitted example mcp model",
      "topics": [
        "demo_fit"
      ]
    },
    {
      "page": "draws-index-mcp",
      "title": "Index 'mcpfit' objects",
      "topics": [
        "draws-index-mcp",
        "nchains",
        "nchains.mcpfit",
        "ndraws",
        "ndraws.mcpfit",
        "niterations",
        "niterations.mcpfit",
        "variables",
        "variables.mcpfit"
      ]
    },
    {
      "page": "execute-mcp-model",
      "title": "Fitted and predicted values of 'mcp' models fits",
      "topics": [
        "execute-mcp-model",
        "fitted",
        "fitted.mcpfit",
        "log_lik",
        "log_lik.mcpfit",
        "predict",
        "predict.mcpfit",
        "residuals",
        "residuals.mcpfit"
      ]
    },
    {
      "page": "hypothesis",
      "title": "Test Hypotheses Concerning Individual Parameters",
      "topics": [
        "hypothesis",
        "hypothesis.mcpfit"
      ]
    },
    {
      "page": "interpolate_newdata",
      "title": "Returns a tibble with all combos of predictors",
      "topics": [
        "interpolate_newdata"
      ]
    },
    {
      "page": "is_mcpfit",
      "title": "Checks if the Argument is an 'mcpfit' Object",
      "topics": [
        "is.mcpfit",
        "is_mcpfit"
      ]
    },
    {
      "page": "loo.mcpfit",
      "title": "Information Criteria for Model Comparison",
      "topics": [
        "LOO",
        "loo",
        "loo.mcpfit",
        "loo_compare",
        "WAIC",
        "waic",
        "waic.mcpfit"
      ]
    },
    {
      "page": "mcp",
      "title": "Fit Multiple Linear Segments And Their Change Points",
      "topics": [
        "mcp"
      ]
    },
    {
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      "title": "Model data columns",
      "topics": [
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      ]
    },
    {
      "page": "mcp_example",
      "title": "Run example models",
      "topics": [
        "mcp_example",
        "mcp_example_data"
      ]
    },
    {
      "page": "mcp_pars",
      "title": "Model parameters",
      "topics": [
        "mcp_pars"
      ]
    },
    {
      "page": "mcp-formula",
      "title": "Model formulas in mcp",
      "topics": [
        "mcp-formula",
        "mcp_formula"
      ]
    },
    {
      "page": "mcp-priors",
      "title": "Priors in mcp",
      "topics": [
        "mcp-priors",
        "mcp_priors"
      ]
    },
    {
      "page": "mcpfit-class",
      "title": "Class 'mcpfit' of Models Fitted with the 'mcp' Package",
      "topics": [
        "mcpfit",
        "mcpfit-class"
      ]
    },
    {
      "page": "model-accessors-mcpfit",
      "title": "Extract Model Information from an 'mcpfit'",
      "topics": [
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        "formula.mcpfit",
        "model-accessors-mcpfit",
        "model.frame.mcpfit",
        "nobs.mcpfit"
      ]
    },
    {
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      "title": "Negative Binomial for mcp",
      "topics": [
        "negbinomial"
      ]
    },
    {
      "page": "plot_pars",
      "title": "Plot individual parameters",
      "topics": [
        "plot_pars"
      ]
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    {
      "page": "plot.mcpfit",
      "title": "Plot full fits",
      "topics": [
        "plot",
        "plot.mcpfit",
        "plot_dpar"
      ]
    },
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      "title": "Posterior prediction draws for 'mcpfit' objects",
      "topics": [
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        "posterior_epred.mcpfit",
        "posterior_linpred",
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        "posterior_predict",
        "posterior_predict.mcpfit"
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    {
      "page": "posterior-uncertainty-mcpfit",
      "title": "Prior and Posterior Covariance and Central Intervals for 'mcpfit' Objects",
      "topics": [
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        "posterior-uncertainty-mcpfit",
        "vcov.mcpfit"
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    },
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      "page": "pp_check",
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        "pp_check.mcpfit"
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      "page": "print.mcplist",
      "title": "Print mcplist",
      "topics": [
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    },
    {
      "page": "print.mcptext",
      "title": "Nice Printing of Multiline Texts",
      "topics": [
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      ]
    },
    {
      "page": "prior_summary",
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      "topics": [
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        "prior_summary.mcpfit"
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    },
    {
      "page": "sd_to_prec",
      "title": "Transform an mcp prior to the parameterization used by JAGS",
      "topics": [
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    },
    {
      "page": "summary.mcpfit",
      "title": "Summarise mcpfit objects",
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