plot_posterior: Plot posterior predictions

In epiforecasts/forecast.vocs: Forecast Case and Sequence Notifications using Variant of Concern Strain Dynamics

Plot posterior predictions

Description

Plot posterior predictions

Usage

plot_posterior(
  posterior,
  obs = NULL,
  forecast_dates = NULL,
  central = FALSE,
  all_obs = FALSE,
  voc_label = "variant of concern"
)

Arguments

posterior	A dataframe of posterior output as produced by fv_tidy_posterior(). For forecast dates to be extracted data with value_type == "cases" must be present.
obs	A data frame of observed data as produced by latest_obs().
forecast_dates	A data.frame in the format produced by extract_forecast_dates() (with at least a date variable and a Data unavailable variable)). Specifies when date availability should be add to plots. May contain faceting variables.
central	Logical, defaults to FALSE. Should the mean and median central estimates be plot as dashed and solid lines respectively. Requires mean and median variables to be present in the input.
all_obs	Logical, defaults to FALSE. Should all observations be plot or just those in the date range of the estimates being plot.
voc_label	Character string giving the name to assign to the variant of concern. Defaults to "variant of concern".

Value

A named list of all supported package plots with sensible defaults.

See Also

Plotting functions add_forecast_dates(), plot.fv_forecast(), plot.fv_posterior(), plot_cases(), plot_default(), plot_growth(), plot_pairs(), plot_rt(), plot_theme(), plot_voc_advantage(), plot_voc_frac(), save_plots()

Examples

posterior <- fv_example(strains = 2, type = "posterior")
plot_posterior(posterior)

epiforecasts/forecast.vocs documentation built on May 14, 2023, 2 p.m.