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首页> 外文期刊>Communications in Mathematical Biology and Neuroscience >Estimation of nonparametric ordinal logistic regression model using local maximum likelihood estimation
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Estimation of nonparametric ordinal logistic regression model using local maximum likelihood estimation

机译:使用局部最大似然估计估计非参数序数逻辑回归模型

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Ordinal logistic regression is a statistical method used to analyze the ordinal response variable with three or more categories and predictor variables that are categorical or continuous. The parametric models for ordinal response variable assume that the predictor is given by a linear form of covariates. In this study, the parametric models are extended to include smooth components based on nonparametric approach. The covariates are modeled as unspecified but smooth functions. Estimation is based on local maximum likelihood estimation (LMLE).
机译:序数逻辑回归是一种统计方法,用于分析与分类或连续的三个或更多类别和预测变量的序数响应变量。 序数响应变量的参数模型假设预测器由线性形式的协变量给出。 在本研究中,参数模型扩展到包括基于非参数方法的平滑组件。 协调因子被建模为未指定但顺利的功能。 估计基于局部最大似然估计(LMLE)。

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