Consistency of AIC and its modification in the growth curve model under a large-(q,n) framework

Q4 Mathematics
R. Enomoto, Tetsuro Sakurai, Y. Fujikoshi
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引用次数: 1

Abstract

The AIC and its modifications have been proposed for selecting the degree in a polynomial growth curve model under a large-sample framework and a high-dimensional framework by Satoh, Kobayashi and Fujikoshi [9] and Fujikoshi, Enomoto and Sakurai [4], respectively. They note that the AIC and its modifications have no consistency property. In this paper we consider asymptotic properties of the AIC and its modification when the number q of groups or explanatory variables and the sample size n are large. First we show that the AIC has a consistency property under a large-(q, n) framework such that q/n → d ∈ [0, 1), under a condition on the noncentrality matrix, but the dimension p is fixed. Next we propose a modification of the AIC (denoted by MAIC) which is an asymptotic unbiased estimator of the risk under the asymptotic framework. It is shown that MAIC has a consistency property under a condition on the noncentrality matrix. Our results are checked numerically by conducting a Mote Carlo simulation. AMS 2010 Mathematics Subject Classification. 62H12, 62H30.
大-(q,n)框架下增长曲线模型中AIC的一致性及其修正
Satoh、Kobayashi和Fujikoshi[9]以及Fujikoshi、Enomoto和Sakurai[4]分别提出了AIC及其修正,用于选择大样本框架和高维框架下多项式生长曲线模型中的度。他们注意到AIC及其修改没有一致性。本文研究了当组或解释变量的数量q和样本量n较大时AIC及其修正的渐近性质。首先,我们证明了AIC在大(q, n)框架下具有一致性,使得q/n→d∈[0,1],在非中心性矩阵的条件下,但维数p是固定的。接下来,我们提出了对AIC(用MAIC表示)的改进,它是渐近框架下风险的渐近无偏估计量。在非中心性矩阵的一定条件下,证明了MAIC具有一致性。通过进行蒙特卡罗模拟,对我们的结果进行了数值验证。AMS 2010数学学科分类。62H12, 62H30。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
SUT Journal of Mathematics
SUT Journal of Mathematics Mathematics-Mathematics (all)
CiteScore
0.30
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