MetaculR (version 0.4.1)

MetaculR_probabilistic_consensus: Generate probabilistic consensus from multiple parameterized forecasts

Description

Generate probabilistic consensus from multiple parameterized forecasts

Usage

MetaculR_probabilistic_consensus(f)

Arguments

f

A list of forecasts (see example for necessary structure).

Value

A list of forecasts.

pdf

A dataframe of probability density functions corresponding to original forecasts and consensus forecast.

cdf

A dataframe of cumulative distribution functions corresponding to original forecasts and consensus forecast.

summary

A dataframe of summary statistics corresponding to original forecasts and consensus forecast, i.e., 10th, 25th, 50th, 75th, 90th centiles and mean.

References

McAndrew, T., & Reich, N. G. (2020). An expert judgment model to predict early stages of the COVID-19 outbreak in the United States [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2020.09.21.20196725

Examples

# NOT RUN {
forecasts <- list(list(range = c(0, 250), resolution = 1),
  list(source = "Pishkalo",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(116, 12),
    weight = 0.2),
  list(source = "Miao",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(121.5, 32.9)),
  list(source = "Labonville",
    dist = "TPD",
    params = c("min", "mode", "max"),
    values = c(89-14, 89, 89+29)),
  list(source = "NOAA",
    dist = "PCT",
    params = c(0.2, 0.8),
    values = c(95, 130)),
  list(source = "Han",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(228, 40.5)),
  list(source = "Dani",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(159, 22.3)),
  list(source = "Li",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(168, 6.3)),
  list(source = "Singh",
    dist = "Norm",
    params = c("mu", "sd"),
    values = c(89, 9)))

MetaculR_probabilistic_consensus(
  f = forecasts)
# }