Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Romano, Elvira"'
Functional Ordinary Kriging is the most widely used method to predict a curve at a given spatial point. However, uncertainty remains an open issue. In this article a distribution-free prediction method based on two different modulation functions and
Externí odkaz:
http://arxiv.org/abs/2409.20084
Functional data analysis (FDA) and ensemble learning can be powerful tools for analyzing complex environmental time series. Recent literature has highlighted the key role of diversity in enhancing accuracy and reducing variance in ensemble methods.Th
Externí odkaz:
http://arxiv.org/abs/2409.07879
This paper introduces a Random Survival Forest (RSF) method for functional data. The focus is specifically on defining a new functional data structure, the Censored Functional Data (CFD), for dealing with temporal observations that are censored due t
Externí odkaz:
http://arxiv.org/abs/2407.15340
In the era of big data, an ever-growing volume of information is recorded, either continuously over time or sporadically, at distinct time intervals. Functional Data Analysis (FDA) stands at the cutting edge of this data revolution, offering a powerf
Externí odkaz:
http://arxiv.org/abs/2407.05159
Publikováno v:
Stat Comput 34, 191 (2024)
Many conventional statistical and machine learning methods face challenges when applied directly to high dimensional temporal observations. In recent decades, Functional Data Analysis (FDA) has gained widespread popularity as a framework for modeling
Externí odkaz:
http://arxiv.org/abs/2403.15778
Publikováno v:
In Spatial Statistics October 2023 57
Autor:
Menna, Costantino, Felicioni, Licia, Negro, Paolo, Lupíšek, Antonín, Romano, Elvira, Prota, Andrea, Hájek, Petr
Publikováno v:
In Sustainable Cities and Society February 2022 77
Akademický článek
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Publikováno v:
In Structures October 2020 27:371-382
Publikováno v:
In Spatial Statistics October 2020 39