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Orthogonal series density estimation for complex surveys

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  • Shangyuan Ye
  • Ye Liang
  • Ibrahim A. Ahmad

Abstract

We propose an orthogonal series density estimator for complex surveys, where samples are neither independent nor identically distributed. The proposed estimator is proved to be design-unbiased and asymptotically design-consistent. The asymptotic normality is proved under both design and combined spaces. Two data driven estimators are proposed based on the proposed oracle estimator. We show the efficiency of the proposed estimators in simulation studies. A real survey data example is provided for an illustration.

Suggested Citation

  • Shangyuan Ye & Ye Liang & Ibrahim A. Ahmad, 2019. "Orthogonal series density estimation for complex surveys," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 31(2), pages 469-481, April.
    • Handle: RePEc:taf:gnstxx:v:31:y:2019:i:2:p:469-481
    DOI: 10.1080/10485252.2019.1585539
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