2026-06-08T11:05:58Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/502692023-06-23T10:11:49Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Río Bueno , Manuel del
author
Delicado, Pedro
2023-06-20T09:44:05Z
2023-06-20T09:44:05Z
2003-02
1048-5252
10.1080/1048525031000074523
https://hdl.handle.net/20.500.14352/50269
http://www.econ.upf.edu/ca/recerca/paper.php?id=422
We introduce nonparametric density estimators that generalize the classical histogram and frequency polygon. The new estimators are expressed as linear combinations of density functions that are piecewise polynomials, where the coefficients are optimally chosen in order to minimize an approximate version of the integrated square error of the estimator. We establish the asymptotic behaviour of the proposed estimators, and study their performance in a simulation study.
A generalization of histogram type estimators
journal article