Transform cumulative probabilities to fit beta distributions — get_model_input_1exp • tipmap

Transform cumulative probabilities to fit beta distributions

Usage

get_model_input_1exp(cum_probs, w = NULL)

Arguments

cum_probs: Numeric vector, containing cumulative probabilities of weights for one expert, as elicited through the roulette method. Each element of the vector represents one bin in the grid.
w: Numeric vector, upper interval limit of bin (defaults to 1:length(cum_probs) / length(cum_probs)).

Value

Dataframe to be used as input to fit beta distributions by [fit_beta_1exp()].

See also

[get_cum_probs_1exp()] and [fit_beta_1exp()].

Examples

chips <- c(0, 2, 3, 2, 1, 1, 1, 0, 0, 0)
x <- get_cum_probs_1exp(chips)
print(x)
#>  [1] 0.0 0.2 0.5 0.7 0.8 0.9 1.0 1.0 1.0 1.0
y <- get_model_input_1exp(x)
print(y)
#>     w cum_probs
#> 1 0.2       0.2
#> 2 0.3       0.5
#> 3 0.4       0.7
#> 4 0.5       0.8
#> 5 0.6       0.9
#> 6 0.7       1.0