Density deconvolution with associated stationary data

Le Thi Hong Thuy; Cao Xuan Phuong

Applications of Mathematics (2023)

  • Volume: 68, Issue: 5, page 685-708
  • ISSN: 0862-7940

Abstract

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We study the density deconvolution problem when the random variables of interest are an associated strictly stationary sequence and the random noises are i.i.d. with a nonstandard density. Based on a nonparametric strategy, we introduce an estimator depending on two parameters. This estimator is shown to be consistent with respect to the mean integrated squared error. Under additional regularity assumptions on the target function as well as on the density of noises, some error estimates are derived. Several numerical simulations are also conducted to illustrate the efficiency of our method.

How to cite

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Thuy, Le Thi Hong, and Phuong, Cao Xuan. "Density deconvolution with associated stationary data." Applications of Mathematics 68.5 (2023): 685-708. <http://eudml.org/doc/299356>.

@article{Thuy2023,
abstract = {We study the density deconvolution problem when the random variables of interest are an associated strictly stationary sequence and the random noises are i.i.d. with a nonstandard density. Based on a nonparametric strategy, we introduce an estimator depending on two parameters. This estimator is shown to be consistent with respect to the mean integrated squared error. Under additional regularity assumptions on the target function as well as on the density of noises, some error estimates are derived. Several numerical simulations are also conducted to illustrate the efficiency of our method.},
author = {Thuy, Le Thi Hong, Phuong, Cao Xuan},
journal = {Applications of Mathematics},
keywords = {associated process; density deconvolution; nonstandard noise density},
language = {eng},
number = {5},
pages = {685-708},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Density deconvolution with associated stationary data},
url = {http://eudml.org/doc/299356},
volume = {68},
year = {2023},
}

TY - JOUR
AU - Thuy, Le Thi Hong
AU - Phuong, Cao Xuan
TI - Density deconvolution with associated stationary data
JO - Applications of Mathematics
PY - 2023
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 68
IS - 5
SP - 685
EP - 708
AB - We study the density deconvolution problem when the random variables of interest are an associated strictly stationary sequence and the random noises are i.i.d. with a nonstandard density. Based on a nonparametric strategy, we introduce an estimator depending on two parameters. This estimator is shown to be consistent with respect to the mean integrated squared error. Under additional regularity assumptions on the target function as well as on the density of noises, some error estimates are derived. Several numerical simulations are also conducted to illustrate the efficiency of our method.
LA - eng
KW - associated process; density deconvolution; nonstandard noise density
UR - http://eudml.org/doc/299356
ER -

References

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