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Kybernetika 28(5):357-382, 1992.

Adaptive Maximum-likelihood-like Estimation in Linear Models Part 1. Consistency

Jan Ámos Víšek


Abstract:

An adaptive estimator of regression model coefficients based on maximization of kernel estimate of likelihood is proposed. Its consistency (in Part 1) and asymptotic normality (in Part 2) is proved. An asymptotic representation of the estimate implies also its asymptotic efficiency.


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BIB TeX

@article{kyb:1992:5:357-382,

author = {V\'{\i}\v{s}ek, Jan \'{A}mos},

title = {Adaptive Maximum-likelihood-like Estimation in Linear Models Part 1. Consistency},

journal = {Kybernetika},

volume = {28},

year = {1992},

number = {5},

pages = {357-382}

publisher = {{\'U}TIA, AV {\v C}R, Prague },

}


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