{'fraction_non_alphanumeric': 0.017408123791102514, 'fraction_numerical': 0.0, 'mean_word_length': 5.815789473684211, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
On the Robustness of Bayesian Modelling of Location and Scale Structures Using Heavy-Tailed Distributions

For solving conflicting information between data and prior distributions, Bayesian modelling with heavy-tailed distributions is applied. Exploiting properties of regularly varying functions and distribution functions as well as their relationship with the finiteness of the moments, we establish results for both location and shape parameter structures. And, as a side result, rates of convergence are derived.