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pro vyhledávání: '"Pennoni F"'
We derive the observed information matrix of hidden Markov models by the application of the Oakes (1999)'s identity. The method only requires the first derivative of the forward-backward recursions of Baum and Welch (1970), instead of the second deri
Externí odkaz:
http://arxiv.org/abs/1201.5990
We provide a comprehensive overview of latent Markov (LM) models for the analysis of longitudinal categorical data. The main assumption behind these models is that the response variables are conditionally independent given a latent process which foll
Externí odkaz:
http://arxiv.org/abs/1003.2804
Autor:
Pennoni, F
We are working on discrete latent variable models and dealing with model and variable selection algorithms to analyze multiple time-series and panel data with many categorical and continuous variables, including missing values. We are interested in e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::592bcf1bda3a150177b71ac78d6b6e40
http://hdl.handle.net/10281/375311
http://hdl.handle.net/10281/375311
The Latent Class (LC) model is one of the most well-known latent variable models; it is very popular for the analysis of categorical response variables, and it is typically used to cluster subjects, by assuming the existence of individual-specific la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::f3d4f0457be399fcbef4284d7139a0ed
http://hdl.handle.net/10281/355780
http://hdl.handle.net/10281/355780
Flexible statistical models have an important role in explaining the joint distribution of financial returns. In these analyses, it is necessary to consider abrupt switches in the market conditions, especially if the focus is on cryptoassets, the mar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::b4cef5693fa9eda24ba2948bd2c54aac
http://hdl.handle.net/10281/369964
http://hdl.handle.net/10281/369964
Akademický článek
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We consider maximum likelihood estimation of the Latent Class (LC) model, which is formulated through individual discrete latent variables. We explore tempering techniques to overcome the problem of multimodality of the log-likelihood function. A Tem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::cb1c816267f194e107f87d683aafb4fb
http://hdl.handle.net/10281/322706
http://hdl.handle.net/10281/322706
We consider hidden Markov and regime-switching copula models as approaches for state allocation in multiple time-series, where state allocation means the prediction of the latent state characterizing each time occasion based on the observed data. Thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1299::a20d62ac346fb1f9cd88ee28cd235a15
http://hdl.handle.net/10281/329765
http://hdl.handle.net/10281/329765