Innovative Approach to Wind Direction Data Analyses: A Compositional Periodic Spline Representation in Bayes Spaces

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F25%3A39923641" target="_blank" >RIV/00216275:25410/25:39923641 - isvavai.cz</a>
Alternative codes found
RIV/61989592:15310/25:73634592
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-92383-8_41" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-92383-8_41</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-92383-8_41" target="_blank" >10.1007/978-3-031-92383-8_41</a>

Result language
angličtina
Original language name
Innovative Approach to Wind Direction Data Analyses: A Compositional Periodic Spline Representation in Bayes Spaces
Original language description
Analyzing environmental data within their natural sample space is essential for optimizing energy, economics, and transport systems. Wind direction, for example, significantly impacts aircraft landing, power transmission, and wind energy generation. However, its circular nature presents unique challenges. Previous research on wind direction distribution has employed methods such as Newton's optimization of von Mises distribution mixtures, the EM algorithm, and evolutionary algorithms, focusing primarily on the approximation of individual functional observations. In this study, we advanced this field by introducing a compositional periodic spline representation of wind direction data within the Bayes spaces framework. The presented approach is efficient for processing directional data using functional data analysis techniques. Our theoretical framework will be validated on empirical wind direction datasets.
Czech name
—
Czech description
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Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
New Trends in Functional Statistics and Related Fields
ISBN
978-3-031-92382-1
ISSN
1431-1968
e-ISSN
—
Number of pages
8
Pages from-to
337-344
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Novara
Event date
Jun 25, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001545850800041

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