Zobrazeno 1 - 10
of 211
pro vyhledávání: '"Giancaterini, A."'
This paper proposes a Sequential Monte Carlo approach for the Bayesian estimation of mixed causal and noncausal models. Unlike previous Bayesian estimation methods developed for these models, Sequential Monte Carlo offers extensive parallelization op
Externí odkaz:
http://arxiv.org/abs/2501.03945
This paper investigates the performance of the Generalized Covariance estimator (GCov) in estimating and identifying mixed causal and noncausal models. The GCov estimator is a semi-parametric method that minimizes an objective function without making
Externí odkaz:
http://arxiv.org/abs/2306.14653
Autor:
Giancaterini, Francesco, Hecq, Alain
Publikováno v:
In Econometrics and Statistics January 2025 33:1-12
This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is
Externí odkaz:
http://arxiv.org/abs/2205.07579
Autor:
Giancaterini, Francesco, Hecq, Alain
The properties of Maximum Likelihood estimator in mixed causal and noncausal models with a generalized Student's t error process are reviewed. Several known existing methods are typically not applicable in the heavy-tailed framework. To this end, a n
Externí odkaz:
http://arxiv.org/abs/2012.01888
Publikováno v:
Journal of American College Health; Jan2025, Vol. 73 Issue 1, p348-356, 9p
Publikováno v:
Statistics & Computing; Aug2024, Vol. 34 Issue 4, p1-20, 20p
Autor:
F. Andreozzi, R. Candido, S. Corrao, R. Fornengo, A. Giancaterini, P. Ponzani, M. C. Ponziani, F. Tuccinardi, D. Mannino
Publikováno v:
Diabetology & Metabolic Syndrome, Vol 12, Iss 1, Pp 1-11 (2020)
Abstract Diabetes mellitus is a chronic disease characterized by high social, economic and health burden, mostly due to the high incidence and morbidity of diabetes complications. Numerous studies have shown that optimizing metabolic control may redu
Externí odkaz:
https://doaj.org/article/458a56c58ef542f5b42d3b0b2464af72
Publikováno v:
Econometrics, Vol 10, Iss 4, p 36 (2022)
This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is
Externí odkaz:
https://doaj.org/article/99535cfb11ae4a35b3c74dba76942ca3
Autor:
Musacchio, Nicoletta, Giancaterini, Annalisa, Guaita, Giacomo, Ozzello, Alessandro, Pellegrini, Maria A, Ponzani, Paola, Russo, Giuseppina T, Zilich, Rita, de Micheli, Alberto
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 6, p e16922 (2020)
Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are no
Externí odkaz:
https://doaj.org/article/8af760bd8ee34239a5dffdc4a4ec8c16