Kernel distribution estimation for grouped data
Use este enlace para citar
http://hdl.handle.net/2183/34341
A non ser que se indique outra cousa, a licenza do ítem descríbese como Atribución-NoComercial-SinDerivadas 3.0 España
Coleccións
- GI-MODES - Artigos [144]
Metadatos
Mostrar o rexistro completo do ítemTítulo
Kernel distribution estimation for grouped dataData
2019Cita bibliográfica
Reyes, M. [et al.]. Kernel distribution estimation for grouped data. Sort: Statistics and Operations Research Transactions, 2019, Vol. 43, Nº. 2, 2019, p. 259-288
Resumo
[Abstract]: Interval-grouped data appear when the observations are not obtained in continuous time, but
monitored in periodical time instants. In this framework, a nonparametric kernel distribution esti-
mator is proposed and studied. The asymptotic bias, variance and mean integrated squared error
of the new approach are derived. From the asymptotic mean integrated squared error, a plug-in
bandwidth is proposed. Additionally, a bootstrap selector to be used in this context is designed.
Through a comprehensive simulation study, the behaviour of the estimator and the bandwidth se-
lectors considering different scenarios of data grouping is shown. The performance of the different
approaches is also illustrated with a real grouped emergence data set of Avena sterilis (wild oat).
Palabras chave
Bootstrap bandwidth
Cumulative distribution function estimator
Interval data
Plug-in bandwidth
Cumulative distribution function estimator
Interval data
Plug-in bandwidth
Versión do editor
Dereitos
Atribución-NoComercial-SinDerivadas 3.0 España
ISSN
1696-2281