Density estimation via best -approximation on classes of step functions
Kybernetika (2017)
- Volume: 53, Issue: 2, page 198-219
- ISSN: 0023-5954
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topFerger, Dietmar, and Venz, John. "Density estimation via best $L^2$-approximation on classes of step functions." Kybernetika 53.2 (2017): 198-219. <http://eudml.org/doc/288220>.
@article{Ferger2017,
abstract = {We establish consistent estimators of jump positions and jump altitudes of a multi-level step function that is the best $L^2$-approximation of a probability density function $f$. If $f$ itself is a step-function the number of jumps may be unknown.},
author = {Ferger, Dietmar, Venz, John},
journal = {Kybernetika},
keywords = {argmin-theorem; density estimation; step functions; martingale inequalities; multivariate cadlag stochastic processes},
language = {eng},
number = {2},
pages = {198-219},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Density estimation via best $L^2$-approximation on classes of step functions},
url = {http://eudml.org/doc/288220},
volume = {53},
year = {2017},
}
TY - JOUR
AU - Ferger, Dietmar
AU - Venz, John
TI - Density estimation via best $L^2$-approximation on classes of step functions
JO - Kybernetika
PY - 2017
PB - Institute of Information Theory and Automation AS CR
VL - 53
IS - 2
SP - 198
EP - 219
AB - We establish consistent estimators of jump positions and jump altitudes of a multi-level step function that is the best $L^2$-approximation of a probability density function $f$. If $f$ itself is a step-function the number of jumps may be unknown.
LA - eng
KW - argmin-theorem; density estimation; step functions; martingale inequalities; multivariate cadlag stochastic processes
UR - http://eudml.org/doc/288220
ER -
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