Second-order asymptotic efficiency of PMLE in generalized linear models
AbstractIn this paper, the author discusses the second-order asymptotic efficiency of pseudo-maximum likelihood estimator of [beta] based on Yi = f(Xi, [beta]) + g(Ti) + [epsilon]i, I = 1, ..., n, where Xi, Ti, [epsilon]i are independent, (Â·, Â·) is known, but g is unknown, [epsilon] ~ [phi](Â·) is known with mean 0 and variance [sigma]2.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 24 (1995)
Issue (Month): 3 (August)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Huang, Tzee-Ming & Chen, Hung, 2008. "Estimating the parametric component of nonlinear partial spline model," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1665-1680, September.
- Song, Lixin & Zhao, Yue & Wang, Xiaoguang, 2010. "Sieve least squares estimation for partially nonlinear models," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1271-1283, September.
- Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
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