An adaptive method for bandwidth selection in circular kernel density estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F24%3A00560521" target="_blank" >RIV/60162694:G42__/24:00560521 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14310/23:00134765

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s00180-023-01401-0" target="_blank" >https://link.springer.com/article/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>

Jazyk výsledku

angličtina

Název v původním jazyce

An adaptive method for bandwidth selection in circular kernel density estimation

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

An adaptive method for bandwidth selection in circular kernel density estimation

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational Statistics

ISSN

0943-4062

e-ISSN

—

Svazek periodika

—

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

20

Strana od-do

—

Kód UT WoS článku

001072240200001

EID výsledku v databázi Scopus

2-s2.0-85173054647