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  "Title": "Markov Chain Monte Carlo Small Area Estimation",
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  "Description": "Fit multi-level models with possibly correlated random\neffects using Markov Chain Monte Carlo simulation. Such models\nallow smoothing over space and time and are useful in, for\nexample, small area estimation.",
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      "page": "mcmcsae-package",
      "title": "Markov Chain Monte Carlo Small Area Estimation",
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        "mcmcsae-package",
        "mcmcsae"
      ]
    },
    {
      "page": "acceptance_rates",
      "title": "Return Metropolis-Hastings acceptance rates",
      "topics": [
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        "custom",
        "iid",
        "RW1",
        "RW2",
        "season",
        "spatial",
        "splines"
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      "title": "Create a sampler object",
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      "topics": [
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      "topics": [
        "gen"
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        "labels.dc",
        "labels<-"
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    },
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      "page": "mc_offset",
      "title": "Create a model component object for an offset, i.e. fixed, non-parametrised term in the linear predictor",
      "topics": [
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    {
      "page": "MCMC-diagnostics",
      "title": "Compute MCMC diagnostic measures",
      "topics": [
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        "n_eff",
        "R_hat"
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    },
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      "title": "Convert a draws component object to another format",
      "topics": [
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        "as.matrix.dc",
        "MCMC-object-conversion",
        "to_draws_array",
        "to_mcmc"
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    {
      "page": "mcmcsae_example",
      "title": "Generate artificial data according to an additive spatio-temporal model",
      "topics": [
        "mcmcsae_example"
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    },
    {
      "page": "MCMCsim",
      "title": "Run a Markov Chain Monte Carlo simulation",
      "topics": [
        "MCMCsim"
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    },
    {
      "page": "mec",
      "title": "Create a model component object for a regression (fixed effects) component in the linear predictor with measurement errors in quantitative covariates",
      "topics": [
        "mec"
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    },
    {
      "page": "model_matrix",
      "title": "Compute possibly sparse model matrix",
      "topics": [
        "model_matrix"
      ]
    },
    {
      "page": "model-information-criteria",
      "title": "Compute DIC, WAIC and leave-one-out cross-validation model measures",
      "topics": [
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        "compute_WAIC",
        "loo.mcdraws",
        "model-information-criteria",
        "waic.mcdraws"
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      "title": "Get the number of chains, samples per chain or the number of variables in a simulation object",
      "topics": [
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        "n_chains-n_draws-n_vars",
        "n_draws",
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      "page": "negbin_control",
      "title": "Set computational options for the sampling algorithms",
      "topics": [
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      "page": "par_names",
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      "topics": [
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      "page": "plot_coef",
      "title": "Plot a set of model coefficients or predictions with uncertainty intervals based on summaries of simulation results or other objects.",
      "topics": [
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      "page": "plot.dc",
      "title": "Trace, density and autocorrelation plots for (parameters of a) draws component (dc) object",
      "topics": [
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      "page": "poisson_control",
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      "topics": [
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      "page": "pr_beta",
      "title": "Create an object representing beta prior distributions",
      "topics": [
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      "page": "pr_exp",
      "title": "Create an object representing exponential prior distributions",
      "topics": [
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      "page": "pr_fixed",
      "title": "Create an object representing a degenerate prior fixing a parameter (vector) to a fixed value",
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      "page": "pr_gamma",
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