Bayesian confidence intervals for the mean, var, and std.
data : array_like
alpha : float, optional
mean_cntr, var_cntr, std_cntr : tuple
Each tuple of mean, variance, and standard deviation estimates represent the (center, (lower, upper)) with center the mean of the conditional pdf of the value given the data and (lower, upper) is a confidence interval centered on the median, containing the estimate to a probability alpha.
Converts data to 1-D and assumes all data has the same mean and variance. Uses Jeffrey’s prior for variance and std.
Equivalent to tuple((x.mean(), x.interval(alpha)) for x in mvsdist(dat))
T.E. Oliphant, “A Bayesian perspective on estimating mean, variance, and standard-deviation from data”, http://hdl.handle.net/1877/438, 2006.