distr function

Specify a general marginal distribution

distr() is used within the function add_integration() to specify marginal distributions for the covariates, via a corresponding inverse CDF. It is also used in predict.stan_nma() to specify a distribution for the baseline response (intercept) when predicting absolute outcomes.

distr(qfun, ...)

Arguments

• qfun: an inverse CDF, either as a function name or a string
• ...: parameters of the distribution as arguments to qfun, these will be quoted and evaluated later in the context of the aggregate data sources

Returns

An object of class distr .

Details

The function qfun should have a formal argument called p. This restriction serves as a crude check for inverse CDFs (e.g. an error will be given if dnorm is used instead of qnorm). If a user-written CDF is supplied, it must have an argument p which takes a vector of probabilities.

Examples

## Specifying marginal distributions for integration

df <- data.frame(x1_mean = 2, x1_sd = 0.5, x2 = 0.8)

# Distribution parameters are evaluated in the context of the data frame
add_integration(df,
                x1 = distr(qnorm, mean = x1_mean, sd = x1_sd),
                x2 = distr(qbern, prob = x2),
                cor = diag(2))

See Also

add_integration() where distr() is used to specify marginal distributions for covariates to integrate over, and predict.stan_nma()

where distr() is used to specify a distribution on the baseline response.