Statistical inference for a varying-coefficient partially nonlinear model with measurement errors

Q Mathematics

Statistical Methodology Pub Date : 2016-09-01 DOI:10.1016/j.stamet.2016.05.004

Yunyun Qian, Zhensheng Huang

引用次数: 9

Abstract

In this study a varying-coefficient partially nonlinear model with measurement errors in the nonparametric part is proposed. Based on the corrected profile least-squared estimation methodology, we define the estimates of the unknowns of the current models, and check whether the coefficient functions are a constant or not by using the popular generalized likelihood ratio (GLR) test method. Further, the corresponding asymptotic distribution is established and a bootstrap procedure is also employed to implement the proposed methodology. Simulated and real examples are given to illustrate our proposed methodology.

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具有测量误差的变系数部分非线性模型的统计推断

本文提出了一种具有非参数部分测量误差的变系数部分非线性模型。基于修正的轮廓最小二乘估计方法，我们定义了当前模型的未知量的估计，并使用流行的广义似然比(GLR)检验方法检查系数函数是否为常数。进一步，建立了相应的渐近分布，并采用自举方法来实现所提出的方法。仿真和实际的例子说明了我们所提出的方法。

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

Statistical Methodology STATISTICS & PROBABILITY-

CiteScore

0.59

自引率

0.00%

发文量

期刊介绍： Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.