- mean
A numeric of the mean (expectation) of the probability
distribution.
- mean_ci_limits
A numeric vector of length two of the confidence
interval around the mean.
- mean_ci
A numeric specifying the confidence interval width,
e.g. 95 would be the 95% CI
- sd
A numeric of the standard deviation of the probability
distribution.
- sd_ci_limits
A numeric vector of length 2 of the confidence interval
around the standard deviation.
- sd_ci
A numeric specifying the confidence interval width,
e.g. 95 would be 95% confidence interval.
- median
A numeric of the median of the probability distribution.
- median_ci_limits
A numeric vector of length two of the confidence
interval around the median.
- median_ci
A numeric specifying the confidence interval width
of the median.
- dispersion
A numeric of the dispersion of the probability
distribution. Important this is the dispersion for probability
distributions that are not usually parameterised by a dispersion parameter,
for example a lognormal distribution. If a probability distribution is
usually parameterised with a dispersion parameter, e.g. negative binomial
distribution, then this should be considered a parameter and not a summary
statistic and should go in the prob_distribution argument when
constructing an <epiparameter> object with epiparameter()
(see create_prob_distribution()).
- dispersion_ci_limits
A numeric vector of length 2 of the confidence
interval around the dispersion.
- dispersion_ci
A numeric specifying the confidence interval width,
e.g. 95 would be 95% confidence interval.
- lower_range
The lower range of the data, used to infer the parameters
of the distribution when not provided.
- upper_range
The upper range of the data, used to infer the parameters
of the distribution when not provided.
- quantiles
A numeric vector of the quantiles for the distribution.
If quantiles are not provided a default empty vector with the 2.5th, 5th,
25th, 75th, 95th, 97.5th quantiles are supplied.