univariate_analysis

univariate_analysis(
    data,
    distribution,
    sampler='DEMCz',
    iterations=3000,
    output_length=10000,
    credible_level=0.9,
    seed=12345,
    exceedance_probabilities=None,
    thinning_interval=-1,
)

Bayesian univariate frequency analysis.

Fit distribution to data with a Bayesian MCMC analysis and return the frequency (quantile) curve, the posterior mean and credible band, and goodness-of-fit scalars. The MCMC warmup (burn-in) length is set automatically to max(50, iterations // 2) and is not a user parameter.

Parameters

Name	Type	Description	Default
data	array_like	Observations to fit.	required
distribution	str	Distribution family name.	required
sampler	('DEMCz', 'DEMCzs', 'ARWMH', 'NUTS')	MCMC sampler.	"DEMCz"
iterations	int	Number of post-warmup MCMC iterations.	3000
output_length	int	Number of posterior samples used to build the credible band.	10000
credible_level	float	Credible-interval width (e.g. 0.90 for a 90% band).	0.90
seed	int	PRNG seed for the sampler.	12345
exceedance_probabilities	array_like of float	Exceedance probabilities at which to tabulate the curve; when None, the default ordinates are used.	None
thinning_interval	int	MCMC thinning interval; -1 keeps the sampler’s own default.	-1

Returns

Name	Type	Description
	dict	Keys parameters, mode_curve, mean_curve, lower_ci, upper_ci (one value per exceedance ordinate) and the scalars aic, bic, dic, rmse.