Nonlinear wavelet density estimation for truncated and dependent observations

Juan Juan Cai, Han Ying Liang*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this paper, we provide an asymptotic expression for mean integrated squared error (MISE) of nonlinear wavelet density estimator for a truncation model. It is assumed that the lifetime observations form a stationary α-mixing sequence. Unlike for kernel estimator, the MISE expression of the nonlinear wavelet estimator is not affected by the presence of discontinuities in the curves. Also, we establish asymptotic normality of the nonlinear wavelet estimator.

Original languageEnglish
Pages (from-to)587-609
Number of pages23
JournalInternational Journal of Wavelets, Multiresolution and Information Processing
Volume9
Issue number4
DOIs
Publication statusPublished - 1 Jun 2011
Externally publishedYes

Keywords

  • α-mixing
  • asymptotic normality
  • mean integrated squared error
  • Nonlinear wavelet density estimator
  • truncated data

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