论文标题
在广义部分线性模型中的假设检验的偏差分析
Analysis of Deviance for Hypothesis Testing in Generalized Partially Linear Models
论文作者
论文摘要
在这项研究中，我们基于局部多项式拟合开发了用于广义部分线性模型的偏差工具的非参数分析。假设有一个规范的链接，我们提出了对偏差的局部和全局分析的表达式，该表达式承认添加性属性减少了高斯病例中方差分解的分析。提出了基于综合似然函数的卡方检验，以正式测试非参数项是否重要。表明仿真结果可说明所提出的卡方检验，并将其与基于惩罚的花纹的现有程序进行比较。该方法适用于德国德国联邦美联储数据。
In this study, we develop nonparametric analysis of deviance tools for generalized partially linear models based on local polynomial fitting. Assuming a canonical link, we propose expressions for both local and global analysis of deviance, which admit an additivity property that reduces to analysis of variance decompositions in the Gaussian case. Chi-square tests based on integrated likelihood functions are proposed to formally test whether the nonparametric term is significant. Simulation results are shown to illustrate the proposed chi-square tests and to compare them with an existing procedure based on penalized splines. The methodology is applied to German Bundesbank Federal Reserve data.
