R语言 SemiParSampleSel包 SemiParSampleSel-package()函数中文帮助文档(中英文对照)

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SemiParSampleSel-package(SemiParSampleSel)
SemiParSampleSel-package()所属R语言包：SemiParSampleSel

                                        Semiparametric Sample Selection Modelling with Continuous Response
                                         连续反应的半参数样本选择模型

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

SemiParSampleSel provides a function for fitting continuous response sample selection models with semiparametric predictors, including linear and nonlinear effects.
SemiParSampleSel提供了一个函数拟合连续响应样本选择与半参数预测模型，包括线性和非线性效应。


Details

详细信息----------Details----------

SemiParSampleSel provides a function for flexible sample selection modelling with continuous response. The underlying representation and  estimation of the model is based on a penalized regression spline approach, with automatic smoothness selection. The numerical routine carries  out function minimization using a trust region algorithm from the package trust in combination  with an adaptation of a low level smoothness selection fitting procedure from the package mgcv combined with a "leapfrog" algorithm.
SemiParSampleSel提供了一个灵活的样本选择模型的连续反应。相关的代表性和被处罚的回归样条曲线的方法，选择自动平滑模型估计的基础上。数值程序进行功能最小化的信赖域算法套件“trust结合适应的较低水平平滑选装程序从包中mgcv”跨越式“算法相结合。

SemiParSampleSel supports the use of many smoothers as extracted from mgcv. Scale invariant tensor product smooths are not currently supported. Estimation is by penalized maximum likelihood with automatic smoothness selection by approximate Un-Biased Risk Estimator (UBRE) score.
SemiParSampleSel支持使用很多平滑提取mgcv。尺度不变的张量积平滑目前不支持。估计是惩罚最大似然选择自动平滑近似无偏的的的风险估算（UBRE）得分。

Confidence intervals for smooth components are derived using a Bayesian approach. Approximate p-values for testing  individual smooth terms for equality to the zero function are also provided. Functions plot.SemiParSampleSel and  summary.SemiParSampleSel extract such information from a fitted SemiParSampleSelObject. Model/variable selection is also  possible via the use of shrinakge smoothers or information criteria.
使用贝叶斯方法得出的置信区间平滑分量。约的p值测试个人光滑的条款平等零功能也有提供。功能plot.SemiParSampleSel和summary.SemiParSampleSel提取这些信息从一个装有SemiParSampleSelObject。也可以通过使用shrinakge平滑或信息标准模型/变量选择。


（作者）----------Author(s)----------



Giampiero Marra (University College London) and Rosalba Radice (London School of Hygiene and Tropical Medicine)

Maintainer: Giampiero Marra <a href="mailto:giampiero@stats.ucl.ac.uk">giampiero@stats.ucl.ac.uk</a>




参考文献----------References----------



参见----------See Also----------

SemiParSampleSel
SemiParSampleSel

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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