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Minimum disparity computation via the iteratively reweighted least integrated squares algorithms

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  • Wang, Yong

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  • Wang, Yong, 2007. "Minimum disparity computation via the iteratively reweighted least integrated squares algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5662-5672, August.
  • Handle: RePEc:eee:csdana:v:51:y:2007:i:12:p:5662-5672
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    References listed on IDEAS

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    1. Ayanendranath Basu & Bruce Lindsay, 1994. "Minimum disparity estimation for continuous models: Efficiency, distributions and robustness," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(4), pages 683-705, December.
    2. Warwick, J., 2005. "A data-based method for selecting tuning parameters in minimum distance estimators," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 571-585, March.
    3. Basu, Ayanendranath & Lindsay, Bruce G., 2004. "The iteratively reweighted estimating equation in minimum distance problems," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 105-124, March.
    4. Wang, Yong, 2007. "Maximum likelihood computation based on the Fisher scoring and Gauss-Newton quadratic approximations," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3776-3787, May.
    5. Karlis, Dimitris & Xekalaki, Evdokia, 1998. "Minimum Hellinger distance estimation for Poisson mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 81-103, November.
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    1. Takada, Teruko, 2009. "Simulated minimum Hellinger distance estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2390-2403, April.
    2. Jiménez-Gamero, M.D. & Pino-Mejías, R. & Alba-Fernández, V. & Moreno-Rebollo, J.L., 2011. "Minimum [phi]-divergence estimation in misspecified multinomial models," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3365-3378, December.
    3. Chee, Chew-Seng, 2017. "A mixture model-based nonparametric approach to estimating a count distribution," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 34-44.

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