Make a prior distribution from priors

Create a `n_param`x `n_draws` database of possible lambda draws to be attached to the model.

Usage

make_prior_distribution(model, n_draws = 4000)

Arguments

model

A causal_model. A model object generated by make_model.

n_draws

A scalar. Number of draws.

Value

A `data.frame` with dimension `n_param`x `n_draws` of possible lambda draws

See also

Other prior_distribution: get_prior_distribution(), set_prior_distribution()

Examples

make_model('X -> Y') %>% make_prior_distribution(n_draws = 5)
#> Summary statistics of model parameter prior distributions:
#> Dimensions: 5 rows (draws) by 6 cols (parameters) 
#> 
#> Summary: 
#> 
#>      mean   sd
#> X.0  0.33 0.25
#> X.1  0.67 0.25
#> Y.00 0.10 0.05
#> Y.10 0.22 0.24
#> Y.01 0.43 0.33
#> Y.11 0.25 0.31