Wavelet Estimation of a Density From Observations of Almost Periodically Correlated Process Under Positive Quadrant Dependence

Moussa Kone and Vincent Monsan

International Journal of Statistics and Probability, 2025, vol. 12, issue 2, 1

Abstract: In this paper, we construct a new wavelet estimator of density for the component of a finite mixture under positive quadrant dependence. Our sample is extracted from almost periodically correlated processes. To evaluate our estimator we will determine a convergence speed from an upper bound for the mean integrated squared error (MISE). Our result is compared to the independent case which provides an optimal convergence rate.

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ccsenet.org/journal/index.php/ijsp/article/download/0/0/48415/52101 (application/pdf)
https://ccsenet.org/journal/index.php/ijsp/article/view/0/48415 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:ijspjl:v:12:y:2025:i:2:p:1

Access Statistics for this article

More articles in International Journal of Statistics and Probability from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().