Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Villa, Cristiano"'
The construction of objective priors is, at best, challenging for multidimensional parameter spaces. A common practice is to assume independence and set up the joint prior as the product of marginal distributions obtained via "standard" objective met
Externí odkaz:
http://arxiv.org/abs/2302.02950
Publikováno v:
In Journal of Statistical Planning and Inference July 2024 231
Autor:
Walker, Stephen G., Villa, Cristiano
In this paper we introduce a novel objective prior distribution levering on the connections between information, divergence and scoring rules. In particular, we do so from the starting point of convex functions representing information in density fun
Externí odkaz:
http://arxiv.org/abs/2105.03241
Motivated by the proliferation of extensive macroeconomic and health datasets necessitating accurate forecasts, a novel approach is introduced to address Vector Autoregressive (VAR) models. This approach employs the global-local shrinkage-Wishart pri
Externí odkaz:
http://arxiv.org/abs/2103.12900
Publikováno v:
In Econometrics and Statistics April 2024
$n$-gram profiles have been successfully and widely used where long sequences of potentially differing lengths are analysed for clustering or classification. Mostly, machine learning algorithms have been used for this purpose but, despite their super
Externí odkaz:
http://arxiv.org/abs/2011.11558
Cyber security is an important concern for all individuals, organisations and governments globally. Cyber attacks have become more sophisticated, frequent and dangerous than ever, and traditional anomaly detection methods have been proved to be less
Externí odkaz:
http://arxiv.org/abs/2003.10360
Gaussian graphical models play an important role in various areas such as genetics, finance, statistical physics and others. They are a powerful modelling tool which allows one to describe the relationships among the variables of interest. From the B
Externí odkaz:
http://arxiv.org/abs/1812.05531
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
We propose a prior distribution for the number of components of a finite mixture model. The novelty is that the prior distribution is obtained by considering the loss one would incur if the true value representing the number of components were not co
Externí odkaz:
http://arxiv.org/abs/1807.07874