R语言-mgcv包-gam()函数中文帮助文档(中英文对照).docx

1、Generalized additive models with integrated smoothness estimation 广义加性模型与集成的平滑估计描述-Description-Fits a generalized additive model (GAM) to data, the term GAM being taken to include any quadratically penalized GLM. The degree of smoothness of model terms is estimated as part of fitting. gam can also f

2、it any GLM subject to multiple quadratic penalties (includingestimation of degree of penalization). Isotropic or scale invariant smooths of any number of variables are available as model terms, as are linear functionals of such smooths; confidence/credible intervals are readily available for any qua

3、ntity predicted using a fitted model; gam is extendable: users can add smooths.适合一个广义相加模型（GAM）的数据，“GAM”被视为包括任何二次处罚GLM。模型计算的平滑度估计作为拟合的一部分。 gam也可以适用于任何GLM多个二次处罚（包括估计程度的处罚）。各向同性或规模不变平滑的任意数量的变量的模型计算，这样的线性泛函平滑的信心/可信区间都是现成的使用拟合模型预测任何数量，“gam是可扩展的：用户可以添加平滑。Smooth terms are represented using penalized regres

4、sion splines (or similar smoothers) with smoothing parameters selected by GCV/UBRE/AIC/REML or by regression splines with fixed degrees of freedom (mixtures of the two are permitted). Multi-dimensional smooths areavailable using penalized thin plate regression splines (isotropic) or tensor product s

5、plines(when an isotropic smooth is inappropriate). For an overview of the smooths available see smooth.terms.For more on specifying models see gam.models, random.effects and linear.functional.terms. For more on model selection see gam.selection. Do read gam.check and choose.k.平滑术语表示使用惩罚回归花键（或类似的平滑）与

6、由GCV / UBRE的/ AIC / REML或由固定的自由度（两个的混合物被允许）的的回归花键与选择的平滑化参数。多维平滑可使用惩罚薄板回归样条曲线（各向同性）或张量积样条线（各向同性的光滑是不恰当的）。的平滑的概述，请参阅smooth.terms。欲了解更多有关指定模型gam.models，random.effects和linear.functional.terms。模型选择的更多信息，请参阅gam.selection。不要读为gam.check和choose.k。See gam from package gam, for GAMs via the original Hastie and

7、 Tibshirani approach (see details for differences to this implementation).见GAM包gam，GAMS通过原来的Hastie和Tibshirani方法（详情请参阅本实施方案的差异）。For very large datasets see bam, for mixed GAM see gamm and random.effects.对于非常大的数据集，请参阅bam，混合GAM看到gamm和random.effects。用法-Usage-gam(formula,family=gaussian(),data=list(),wei

8、ghts=NULL,subset=NULL, na.action,offset=NULL,method=GCV.Cp, optimizer=c(outer,newton),control=list(),scale=0, select=FALSE,knots=NULL,sp=NULL,min.sp=NULL,H=NULL,gamma=1, fit=TRUE,paraPen=NULL,G=NULL,in.out,.)参数-Arguments-参数：formulaA GAM formula (see formula.gam and also gam.models).This is exactly l

9、ike the formula for a GLM except that smooth terms, s and te can be addedto the right hand side to specify that the linear predictor depends on smooth functions of predictors(or linear functionals of these). 一个GAM的公式（见formula.gam和gam.models）。这是完全一样的公式，除非GLM那光滑的条款，s和te可以被添加到指定的线性预测依赖于光滑函数的预测（或线性泛函的右手

10、边这些）。参数：familyThis is a family object specifying the distribution and link to use in fitting etc. See glm and family for more details. A negative binomial family is provided: see negbin.quasi families actually result in the use of extended quasi-likelihoodif method is set to a RE/ML method (McCullag

11、h and Nelder, 1989, 9.6). 这是一个家庭对象指定的分配和使用链接配件等glm和family更多的细节。负二项分布家庭提供：看到negbin。 quasi家庭实际上导致在使用扩展的拟似然method设置为一个RE / ML方法（McCullagh和Nelder，1989年，9.6）。参数：dataA data frame or list containing the model response variable andcovariates required by the formula. By default the variables are takenfrom en

12、vironment(formula): typically the environment fromwhich gam is called.式所需的一个数据框或列表包含模型响应变量，协变量。默认情况下，变量从environment(formula)：gam被称为典型的环境。参数：weightsprior weights on the data.现有的数据上的权重。参数：subsetan optional vector specifying a subset of observations to be used in the fitting process.一个可选的矢量指定的装配过程中可以使用

13、的观测值的一个子集。参数：na.actiona function which indicates what should happen when the data contain NAs.The default is set by the na.action setting of options, and is na.fail if that is unset.The “factory-fresh” default is na.omit.一个函数，它表示时会发生什么数据包含“NA”。默认设置是“na.action设置选项，na.fail”如果是没有设置的。 “工厂新鲜的

14、”默认“na.omit。参数：offsetCan be used to supply a model offset for use in fitting. Note that this offset will always be completely ignored when predicting, unlike an offsetincluded in formula: this conforms to the behaviour of lm and glm.可以用来提供一个模型偏移量用于接头。请注意，此偏移量总是被完全忽略当预测，不像一个偏移量包含在formula：这符合的lm和glm的行

15、为。参数：controlA list of fit control parameters to replace defaults returned bygam.control. Values not set assume default values.一个合适的控制参数，以取代默认值返回gam.control。未设置假设值默认值。参数：methodThe smoothing parameter estimation method. GCV.Cp to use GCV for unknown scale parameter and Mallows Cp/UBRE/AIC for known scale. GACV.Cp is equivalent, but using GACV in place of GCV. REMLfor REML estimation, including of unknown scale, P-REML for REML estimation, but using a Pearson estimateo