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    {
      "page": "gam_knots",
      "title": "Derive a set of knot points for a GAM from data",
      "concept": [
        "models"
      ],
      "topics": [
        "gam_knots"
      ]
    },
    {
      "page": "gam_nb_model_fn",
      "title": "Default GAM count negative binomial model.",
      "concept": [
        "models"
      ],
      "topics": [
        "gam_nb_model_fn"
      ]
    },
    {
      "page": "gam_poisson_model_fn",
      "title": "Default GAM count model.",
      "concept": [
        "models"
      ],
      "topics": [
        "gam_poisson_model_fn"
      ]
    },
    {
      "page": "geom_events",
      "title": "Add time series event markers to a time series plot.",
      "concept": [
        "vis"
      ],
      "topics": [
        "geom_events"
      ]
    },
    {
      "page": "growth_rate_from_incidence",
      "title": "Estimate growth rate from modelled incidence",
      "concept": [
        "models"
      ],
      "topics": [
        "growth_rate_from_incidence"
      ]
    },
    {
      "page": "growth_rate_from_prevalence",
      "title": "Estimate relative growth rate from estimated prevalence",
      "concept": [
        "models"
      ],
      "topics": [
        "growth_rate_from_prevalence"
      ]
    },
    {
      "page": "growth_rate_from_proportion",
      "title": "Estimate relative growth rate from modelled proportion",
      "concept": [
        "models"
      ],
      "topics": [
        "growth_rate_from_proportion"
      ]
    },
    {
      "page": "infer_population",
      "title": "Infers a daily baseline population for a timeseries",
      "concept": [
        "models"
      ],
      "topics": [
        "infer_population"
      ]
    },
    {
      "page": "infer_prevalence",
      "title": "Infer the prevalence of disease from incidence estimates and population size.",
      "concept": [
        "models"
      ],
      "topics": [
        "infer_prevalence"
      ]
    },
    {
      "page": "infer_rate_ratio",
      "title": "Calculate a risk ratio from incidence",
      "concept": [
        "models"
      ],
      "topics": [
        "infer_rate_ratio"
      ]
    },
    {
      "page": "infer_risk_ratio",
      "title": "Calculate a normalised risk ratio from proportions",
      "concept": [
        "models"
      ],
      "topics": [
        "infer_risk_ratio"
      ]
    },
    {
      "page": "integer_breaks",
      "title": "Strictly integer breaks for continuous scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "integer_breaks"
      ]
    },
    {
      "page": "inv_wallinga_lipsitch",
      "title": "Calculate a growth rate from a reproduction number and an infectivity profile,",
      "concept": [
        "models"
      ],
      "topics": [
        "inv_wallinga_lipsitch"
      ]
    },
    {
      "page": "is.Date",
      "title": "Check whether vector is a date",
      "concept": [
        "time_period"
      ],
      "topics": [
        "is.Date"
      ]
    },
    {
      "page": "julian.time_period",
      "title": "Extract Parts of a POSIXt or Date Object",
      "concept": [
        "time_period"
      ],
      "topics": [
        "julian.time_period"
      ]
    },
    {
      "page": "labels.time_period",
      "title": "Label a time period",
      "concept": [
        "time_period"
      ],
      "topics": [
        "labels.time_period"
      ]
    },
    {
      "page": "linelist",
      "title": "Coerce an object to a 'ggoutbreak' compatible case linelist.",
      "concept": [
        "models"
      ],
      "topics": [
        "linelist"
      ]
    },
    {
      "page": "logit_trans",
      "title": "logit scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "logit_trans"
      ]
    },
    {
      "page": "make_empirical_ip",
      "title": "Recover a long format infectivity profile from an 'EpiEstim' style matrix",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "make_empirical_ip"
      ]
    },
    {
      "page": "make_fixed_ip",
      "title": "Generate a simple discrete infectivity profile from a gamma distribution",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "make_fixed_ip"
      ]
    },
    {
      "page": "make_gamma_ip",
      "title": "Make an infectivity profile from published data",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "make_gamma_ip"
      ]
    },
    {
      "page": "make_posterior_ip",
      "title": "Make an infectivity profile from posterior samples",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "make_posterior_ip"
      ]
    },
    {
      "page": "make_resampled_ip",
      "title": "Re-sample an empirical IP distribution direct from data",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "make_resampled_ip"
      ]
    },
    {
      "page": "max_date",
      "title": "The maximum of a set of dates",
      "concept": [
        "time_period"
      ],
      "topics": [
        "max_date"
      ]
    },
    {
      "page": "min_date",
      "title": "The minimum of a set of dates",
      "concept": [
        "time_period"
      ],
      "topics": [
        "min_date"
      ]
    },
    {
      "page": "months.time_period",
      "title": "Extract Parts of a POSIXt or Date Object",
      "concept": [
        "time_period"
      ],
      "topics": [
        "months.time_period"
      ]
    },
    {
      "page": "multinomial_nnet_model",
      "title": "Multinomial time-series model.",
      "concept": [
        "models"
      ],
      "topics": [
        "multinomial_nnet_model"
      ]
    },
    {
      "page": "normalise_count",
      "title": "Calculate a normalised count per capita",
      "concept": [
        "models"
      ],
      "topics": [
        "normalise_count"
      ]
    },
    {
      "page": "normalise_incidence",
      "title": "Calculate a normalised incidence rate per capita",
      "concept": [
        "models"
      ],
      "topics": [
        "normalise_incidence"
      ]
    },
    {
      "page": "omega_matrix",
      "title": "Generate a infectivity profile matrix from a long format",
      "concept": [
        "delay_distribution"
      ],
      "topics": [
        "omega_matrix"
      ]
    },
    {
      "page": "pbeta2",
      "title": "The Beta Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pbeta2"
      ]
    },
    {
      "page": "pcgamma",
      "title": "Cumulative probability: gamma distribution constrained to have mean > sd",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pcgamma"
      ]
    },
    {
      "page": "pgamma2",
      "title": "The Gamma Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pgamma2"
      ]
    },
    {
      "page": "plnorm2",
      "title": "The Log Normal Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "plnorm2"
      ]
    },
    {
      "page": "plogitnorm",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "plogitnorm"
      ]
    },
    {
      "page": "plogitnorm2",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "plogitnorm2"
      ]
    },
    {
      "page": "plot_cases",
      "title": "Plot a line-list of cases as a histogram",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_cases"
      ]
    },
    {
      "page": "plot_counts",
      "title": "Plot a raw case count timeseries",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_counts"
      ]
    },
    {
      "page": "plot_growth_phase",
      "title": "Plot an incidence or proportion versus growth phase diagram",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_growth_phase"
      ]
    },
    {
      "page": "plot_growth_rate",
      "title": "Growth rate timeseries diagram",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_growth_rate"
      ]
    },
    {
      "page": "plot_incidence",
      "title": "Plot an incidence timeseries",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_incidence"
      ]
    },
    {
      "page": "plot_ip",
      "title": "Plot an infectivity profile",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_ip"
      ]
    },
    {
      "page": "plot_multinomial",
      "title": "Plot a multinomial proportions model",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_multinomial"
      ]
    },
    {
      "page": "plot_prevalence",
      "title": "Plot a timeseries of disease prevalence",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_prevalence"
      ]
    },
    {
      "page": "plot_proportion",
      "title": "Plot a proportions timeseries",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_proportion"
      ]
    },
    {
      "page": "plot_proportions_data",
      "title": "Plot a raw case count proportion timeseries",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_proportions_data"
      ]
    },
    {
      "page": "plot_rt",
      "title": "Reproduction number timeseries diagram",
      "concept": [
        "vis"
      ],
      "topics": [
        "plot_rt"
      ]
    },
    {
      "page": "pnbinom2",
      "title": "The Negative Binomial Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pnbinom2"
      ]
    },
    {
      "page": "pnull",
      "title": "Null distributions always returns NA",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pnull"
      ]
    },
    {
      "page": "poisson_gam_model",
      "title": "GAM poisson time-series model",
      "concept": [
        "models"
      ],
      "topics": [
        "poisson_gam_model"
      ]
    },
    {
      "page": "poisson_glm_model",
      "title": "Poisson time-series model.",
      "concept": [
        "models"
      ],
      "topics": [
        "poisson_glm_model"
      ]
    },
    {
      "page": "poisson_locfit_model",
      "title": "Poisson time-series model.",
      "concept": [
        "models"
      ],
      "topics": [
        "poisson_locfit_model"
      ]
    },
    {
      "page": "proportion_glm_model",
      "title": "Binomial time-series model.",
      "concept": [
        "models"
      ],
      "topics": [
        "proportion_glm_model"
      ]
    },
    {
      "page": "proportion_locfit_model",
      "title": "A binomial proportion estimate and associated exponential growth rate",
      "concept": [
        "models"
      ],
      "topics": [
        "proportion_locfit_model"
      ]
    },
    {
      "page": "pwedge",
      "title": "Wedge distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "pwedge"
      ]
    },
    {
      "page": "qbeta2",
      "title": "The Beta Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qbeta2"
      ]
    },
    {
      "page": "qcgamma",
      "title": "Quantile: gamma distribution constrained to have mean > sd",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qcgamma"
      ]
    },
    {
      "page": "qgamma2",
      "title": "The Gamma Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qgamma2"
      ]
    },
    {
      "page": "qlnorm2",
      "title": "The Log Normal Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qlnorm2"
      ]
    },
    {
      "page": "qlogitnorm",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qlogitnorm"
      ]
    },
    {
      "page": "qlogitnorm2",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qlogitnorm2"
      ]
    },
    {
      "page": "qnbinom2",
      "title": "The Negative Binomial Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qnbinom2"
      ]
    },
    {
      "page": "qnull",
      "title": "Null distributions always returns NA",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qnull"
      ]
    },
    {
      "page": "quantify_lag",
      "title": "Identify estimate lags in a model",
      "concept": [
        "test"
      ],
      "topics": [
        "quantify_lag"
      ]
    },
    {
      "page": "quarters.time_period",
      "title": "Extract Parts of a POSIXt or Date Object",
      "concept": [
        "time_period"
      ],
      "topics": [
        "quarters.time_period"
      ]
    },
    {
      "page": "qwedge",
      "title": "Wedge distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "qwedge"
      ]
    },
    {
      "page": "rbern",
      "title": "A random Bernoulli sample as a logical value",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rbern"
      ]
    },
    {
      "page": "rbeta2",
      "title": "The Beta Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rbeta2"
      ]
    },
    {
      "page": "rcategorical",
      "title": "Sampling from the multinomial equivalent of the Bernoulli distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rcategorical"
      ]
    },
    {
      "page": "rcgamma",
      "title": "Sampling: gamma distribution constrained to have mean > sd",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rcgamma"
      ]
    },
    {
      "page": "rdiscgamma",
      "title": "Random count data from a discrete gamma distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rdiscgamma"
      ]
    },
    {
      "page": "reband_discrete",
      "title": "Reband any discrete distribution",
      "concept": [
        "wrangling"
      ],
      "topics": [
        "reband_discrete"
      ]
    },
    {
      "page": "rescale_model",
      "title": "Rescale a timeseries in the temporal dimension",
      "concept": [
        "models"
      ],
      "topics": [
        "rescale_model"
      ]
    },
    {
      "page": "rexpgrowth",
      "title": "Randomly sample incident times in an exponentially growing process",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rexpgrowth"
      ]
    },
    {
      "page": "rexpgrowthI0",
      "title": "Randomly sample incident times in an exponentially growing process with initial case load",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rexpgrowthI0"
      ]
    },
    {
      "page": "rgamma2",
      "title": "The Gamma Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rgamma2"
      ]
    },
    {
      "page": "rlnorm2",
      "title": "The Log Normal Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rlnorm2"
      ]
    },
    {
      "page": "rlogitnorm",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rlogitnorm"
      ]
    },
    {
      "page": "rlogitnorm2",
      "title": "Logit-normal distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rlogitnorm2"
      ]
    },
    {
      "page": "rnbinom2",
      "title": "The Negative Binomial Distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rnbinom2"
      ]
    },
    {
      "page": "rnull",
      "title": "Null distributions always returns NA",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rnull"
      ]
    },
    {
      "page": "rt_cori",
      "title": "Reproduction number estimate using the Cori method",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_cori"
      ]
    },
    {
      "page": "rt_epiestim",
      "title": "'EpiEstim' reproduction number wrapper function",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_epiestim"
      ]
    },
    {
      "page": "rt_from_growth_rate",
      "title": "Wallinga-Lipsitch reproduction number from growth rates",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_from_growth_rate"
      ]
    },
    {
      "page": "rt_from_incidence",
      "title": "Reproduction number from modelled incidence",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_from_incidence"
      ]
    },
    {
      "page": "rt_from_renewal",
      "title": "Reproduction number from renewal equation applied to modelled incidence using statistical re-sampling",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_from_renewal"
      ]
    },
    {
      "page": "rt_incidence_reference_implementation",
      "title": "Reference implementation of the Rt from modelled incidence algorithm",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_incidence_reference_implementation"
      ]
    },
    {
      "page": "rt_incidence_timeseries_implementation",
      "title": "Time series implementation of the Rt from modelled incidence algorithm",
      "concept": [
        "models"
      ],
      "topics": [
        "rt_incidence_timeseries_implementation"
      ]
    },
    {
      "page": "rwedge",
      "title": "Wedge distribution",
      "concept": [
        "distributions"
      ],
      "topics": [
        "rwedge"
      ]
    },
    {
      "page": "scale_x_log1p",
      "title": "A log1p x scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "scale_x_log1p"
      ]
    },
    {
      "page": "scale_x_logit",
      "title": "A logit x scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "scale_x_logit"
      ]
    },
    {
      "page": "scale_y_log1p",
      "title": "A log1p y scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "scale_y_log1p"
      ]
    },
    {
      "page": "scale_y_logit",
      "title": "A logit y scale",
      "concept": [
        "vis"
      ],
      "topics": [
        "scale_y_logit"
      ]
    },
    {
      "page": "score_estimate",
      "title": "Calculate scoring statistics from predictions.",
      "concept": [
        "test"
      ],
      "topics": [
        "score_estimate"
      ]
    },
    {
      "page": "set_defaults",
      "title": "Set or reset the default origin and unit for time periods",
      "concept": [
        "time_period"
      ],
      "topics": [
        "set_defaults",
        "set_default_start",
        "set_default_unit",
        "with_defaults"
      ]
    },
    {
      "page": "sim_apply_ascertainment",
      "title": "Apply a ascertainment bias to the observed case counts.",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_apply_ascertainment"
      ]
    },
    {
      "page": "sim_apply_delay",
      "title": "Apply delay distribution to count or linelist data",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_apply_delay"
      ]
    },
    {
      "page": "sim_branching_process",
      "title": "Generate a line list from a branching process model parametrised by reproduction number",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_branching_process"
      ]
    },
    {
      "page": "sim_convolution",
      "title": "Apply a time varying probability and convolution to count data",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_convolution"
      ]
    },
    {
      "page": "sim_delay",
      "title": "Apply a time-varying probability and delay function to linelist data",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_delay"
      ]
    },
    {
      "page": "sim_delayed_observation",
      "title": "Apply a right censoring to count data.",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_delayed_observation"
      ]
    },
    {
      "page": "sim_events",
      "title": "Extract the events dataframe from a simulation output",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_events"
      ]
    },
    {
      "page": "sim_geom_function",
      "title": "The principal input function to a 'ggoutbreak' simulation as a 'ggplot2' layer.",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_geom_function"
      ]
    },
    {
      "page": "sim_multinomial",
      "title": "Generate a multinomial outbreak defined by per class growth rates and a poisson model",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_multinomial"
      ]
    },
    {
      "page": "sim_poisson_model",
      "title": "Generate an outbreak case count series defined by growth rates using a poisson model.",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_poisson_model"
      ]
    },
    {
      "page": "sim_poisson_Rt_model",
      "title": "Generate an outbreak case count series defined by Reproduction number using a poisson model.",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_poisson_Rt_model"
      ]
    },
    {
      "page": "sim_seir_model",
      "title": "SEIR model with time-varying transmission parameter",
      "concept": [
        "test"
      ],
      "topics": [
        "sim_seir_model"
      ]
    },
    {
      "page": "sim_summarise_linelist",
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