Geodesic
Consistency of a Class of Information Criteria for Model Selection in Nonlinear Regression
Teoriâ veroâtnostej i ee primeneniâ, Tome 37 (1992) no. 1, pp. 105-112

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In this paper we prove the consistency in probability of a class of generalized BIC criteria for model selection in nonlinear regression, by using asymptotic results of Gallant. This extends a result obtained by Nishii for model selection in linear regression. 
@article{TVP_1992_37_1_a15,
     author = {D. Haughton},
     title = {Consistency of a {Class} of {Information} {Criteria} for {Model} {Selection} in {Nonlinear} {Regression}},
     journal = {Teori\^a vero\^atnostej i ee primeneni\^a},
     pages = {105--112},
     publisher = {mathdoc},
     volume = {37},
     number = {1},
     year = {1992},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TVP_1992_37_1_a15/}
}
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D. Haughton. Consistency of a Class of Information Criteria for Model Selection in Nonlinear Regression. Teoriâ veroâtnostej i ee primeneniâ, Tome 37 (1992) no. 1, pp. 105-112. http://geodesic.mathdoc.fr/item/TVP_1992_37_1_a15/