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Confidence intervals for probability density functions under strong mixing samples

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  • Qingzhu Lei
  • Yongsong Qin

Abstract

It is shown that the empirical likelihood (EL) ratio statistic for a probability density function (p.d.f.) is asymptotically -type distributed under a strong mixing sample, which is used to obtain an EL-based confidence interval (CI) for the p.d.f. Results of a simulation study on the finite sample performance of the CI are reported.

Suggested Citation

  • Qingzhu Lei & Yongsong Qin, 2015. "Confidence intervals for probability density functions under strong mixing samples," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(2), pages 181-193, June.
    • Handle: RePEc:taf:gnstxx:v:27:y:2015:i:2:p:181-193
    DOI: 10.1080/10485252.2015.1037303
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    References listed on IDEAS

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    1. Roussas, George G., 2000. "Asymptotic normality of the kernel estimate of a probability density function under association," Statistics & Probability Letters, Elsevier, vol. 50(1), pages 1-12, October.
    2. Pham, Tuan D. & Tran, Lanh T., 1985. "Some mixing properties of time series models," Stochastic Processes and their Applications, Elsevier, vol. 19(2), pages 297-303, April.
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