An adaptive method for bandwidth selection in circular kernel density estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00576866" target="_blank" >RIV/67985807:_____/24:00576866 - isvavai.cz</a>
Alternative codes found
RIV/60162694:G42__/24:00560521 RIV/00216224:14310/24:00135217
Result on the web
<a href="https://doi.org/10.1007/s00180-023-01401-0" target="_blank" >https://doi.org/10.1007/s00180-023-01401-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00180-023-01401-0" target="_blank" >10.1007/s00180-023-01401-0</a>
Alternative languages
Result language
angličtina
Original language name
An adaptive method for bandwidth selection in circular kernel density estimation
Original language description
Kernel density estimations of circular data are an effective type of nonparametric estimation. The performance of these estimations depends significantly on a smoothing parameter referred to as bandwidth. Selecting suitable bandwidths for these types of estimation pose fundamental challenges, therefore fixed bandwidth selectors are often the initial choice. The study investigates common bandwidth selection methods and proposes novel methods which adopt the idea from the linear case. The attention is also paid to variable bandwidth selection. Using simulations which incorporate a range of circular distributions that exhibit multimodality, peakedness and skewness, the proposed methods were evaluated and then compared with other bandwidth selectors to determine their potential advantages. Two real datasets, one containing animal movements and the other wind direction data, were applied to illustrate the utility of the proposed methods.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational Statistics
ISSN
0943-4062
e-ISSN
1613-9658
Volume of the periodical
39
Issue of the periodical within the volume
4
Country of publishing house
DE - GERMANY
Number of pages
20
Pages from-to
1709-1728
UT code for WoS article
001072240200001
EID of the result in the Scopus database
2-s2.0-85173054647