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Empirical likelihood inference for partial linear models under martingale difference sequence

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  • Chen, Xia
  • Cui, Hengjian

Abstract

We consider the application of the empirical likelihood method to a partially linear model with martingale difference error. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. Some simulations are conducted to illustrate the proposed method.

Suggested Citation

  • Chen, Xia & Cui, Hengjian, 2008. "Empirical likelihood inference for partial linear models under martingale difference sequence," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2895-2901, December.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:17:p:2895-2901
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    References listed on IDEAS

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    1. Shi, Jian & Lau, Tai-Shing, 2000. "Empirical Likelihood for Partially Linear Models," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 132-148, January.
    2. Chen, S. X., 1994. "Empirical Likelihood Confidence Intervals for Linear Regression Coefficients," Journal of Multivariate Analysis, Elsevier, vol. 49(1), pages 24-40, April.
    3. Qihua Wang & J. N. K. Rao, 2002. "Empirical Likelihood‐based Inference in Linear Models with Missing Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(3), pages 563-576, September.
    4. Song Chen, 1993. "On the accuracy of empirical likelihood confidence regions for linear regression model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(4), pages 621-637, December.
    5. Lin, Lu & Zhang, Runchu, 2001. "Blockwise empirical Euclidean likelihood for weakly dependent processes," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 143-152, June.
    6. Wang, Qi-Hua & Li, Gang, 2002. "Empirical Likelihood Semiparametric Regression Analysis under Random Censorship," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 469-486, November.
    7. Qihua Wang, 2002. "Empirical likelihood-based inference in linear errors-in-covariables models with validation data," Biometrika, Biometrika Trust, vol. 89(2), pages 345-358, June.
    8. Wang, Qi-Hua & Jing, Bing-Yi, 1999. "Empirical likelihood for partial linear models with fixed designs," Statistics & Probability Letters, Elsevier, vol. 41(4), pages 425-433, February.
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    1. Ruidong Han & Xinghui Wang & Shuhe Hu, 2018. "Asymptotics of the weighted least squares estimation for AR(1) processes with applications to confidence intervals," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 479-490, August.

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