Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Tommaso Di Fonzo"'
Autor:
Gianluca Raffaello Damiani, Daniele Di Gennaro, Antonio Malvasi, Antonella Vimercati, Vera Loizzi, Maria Gaetani, Tommaso Di Fonzo, Miriam Dellino, Gerardo Cazzato, Ettore Cicinelli, Giuseppe Trojano
Publikováno v:
Gynecology and Minimally Invasive Therapy, Vol 12, Iss 4, Pp 243-245 (2023)
Endometrial osseous metaplasia (EOM) is an uncommon clinical entity with the presence of bone in the endometrium which requires clinical and therapeutic framework. It is also described by various other names such as endometrial ossification, ectopic
Externí odkaz:
https://doaj.org/article/ba5ec2e727b844578920e44801cb7c65
Autor:
Daniele Girolimetto, Tommaso Di Fonzo
Publikováno v:
Solar Energy. 251:13-29
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8095d7cb8ea6c6790ea938685a9cd1e7
https://doi.org/10.1016/j.solener.2023.01.003
https://doi.org/10.1016/j.solener.2023.01.003
Autor:
Tommaso Di Fonzo, Daniele Girolimetto
Forecast reconciliation is a post-forecasting process aimed to improve the quality of the base forecasts for a system of hierarchical/grouped time series (Hyndman et al., 2011). Contemporaneous (cross-sectional) and temporal hierarchies have been con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7da1759a390c7513c0b78de9450be2f8
https://hdl.handle.net/11577/3403190
https://hdl.handle.net/11577/3403190
Autor:
Daniele Girolimetto, Tommaso Di Fonzo
Publikováno v:
International Journal of Forecasting.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6af9d229899e402abafe77966a7def27
https://doi.org/10.1016/j.ijforecast.2022.07.001
https://doi.org/10.1016/j.ijforecast.2022.07.001
Publikováno v:
Statistica Neerlandica. 72:402-405
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7437ade1a5da8eabb18e246464c869e
https://doi.org/10.1111/stan.12157
https://doi.org/10.1111/stan.12157
Publikováno v:
Statistica Neerlandica. 72:533-552
The 2003–2007 U.S. annual input–output accounts, GDP‐by‐industry accounts, and expenditure‐based GDP are reconciled with the 2002 and 2007 quinquennial benchmarks and all contemporaneous constraints of the input–output accounts for the in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82f6aa40536cbc1c9cda70a7dd0d4b2e
https://doi.org/10.1111/stan.12154
https://doi.org/10.1111/stan.12154
We model the electricity consumption in the market segment that compose the Qatari electricity market. We link electricity consumption to GDP growth and Population Growth. Building on the estimated model, we develop long-range forecasts of electricit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::275f75b5139f8330d9da38f81a29b550
http://hdl.handle.net/11577/3283729
http://hdl.handle.net/11577/3283729
Autor:
Marco Marini, Tommaso Di Fonzo
Publikováno v:
Journal of Economic and Social Measurement. 37:225-252
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce2cf4fdcae9744305a9b55015a6c4b9
https://doi.org/10.3233/jem-2012-0358
https://doi.org/10.3233/jem-2012-0358
Autor:
Marco Marini, Tommaso Di Fonzo
Publikováno v:
Journal of the Royal Statistical Society Series C: Applied Statistics. 60:143-164
Summary The reconciliation of systems of time series subject to both temporal and contemporaneous constraints can be solved in such a way that the temporal profiles of the original series be preserved ‘at best’ (the movement preservation principl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8aaa1bfbc02747684bf70a006c84a70b
https://doi.org/10.1111/j.1467-9876.2010.00733.x
https://doi.org/10.1111/j.1467-9876.2010.00733.x
Autor:
Tommaso Di Fonzo, Marco Marini
We propose new simultaneous and two-step procedures for reconciling systems of time series subject to temporal and contemporaneous constraints according to a growth rates preservation (GRP) principle. The techniques exploit the analytic gradient and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96d9011444348226e71baea609d53696
http://hdl.handle.net/11577/3150731
http://hdl.handle.net/11577/3150731