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R语言 VGAM包 vgam.control()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 15:56:41 | 显示全部楼层 |阅读模式
vgam.control(VGAM)
vgam.control()所属R语言包:VGAM

                                         Control function for vgam
                                         控制为vgam的功能

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Algorithmic constants and parameters for running vgam are set using this function.
算法的常量和运行参数vgam使用此功能。


用法----------Usage----------


vgam.control(all.knots = FALSE, bf.epsilon = 1e-07, bf.maxit = 30,
             checkwz=TRUE, criterion = names(.min.criterion.VGAM),
             epsilon = 1e-07, maxit = 30, na.action = na.fail,
             nk = NULL, save.weight = FALSE, se.fit = TRUE,
             trace = FALSE, wzepsilon = .Machine$double.eps^0.75,
             ...)



参数----------Arguments----------

参数:all.knots
logical indicating if all distinct points of  the smoothing variables are to be used as knots. By default, all.knots=TRUE for n <= 40, and for n > 40, the number of knots is approximately 40 + (n-40)^0.25. This increases very slowly with n so that the number of knots is approximately between 50 and 60 for large n.  
逻辑表示,如果所有的不同的点的平滑变量被用来作为结。默认情况下,all.knots=TRUEn <= 40和n > 40,节点数约为40 + (n-40)^0.25。这增加非常缓慢n的节点数大约是在50和60之间为大n。


参数:bf.epsilon
tolerance used by the modified vector backfitting algorithm for testing convergence. Must be a positive number.  
修改后的向量回切测试算法收敛公差。必须是一个正数。


参数:bf.maxit
maximum number of iterations allowed in the modified vector backfitting algorithm. Must be a positive integer.  
允许改性向量回切算法中的迭代的最大数量。必须是一个正整数。


参数:checkwz
logical indicating whether the diagonal elements of the working weight matrices should be checked whether they are sufficiently positive, i.e., greater than wzepsilon. If not, any values less than wzepsilon are replaced with this value.  
逻辑指示的工作的权重矩阵的对角线元素是否应检查是否有足够的正面,即,大于wzepsilon。如果没有,任何值小于wzepsilon这个值被替换。


参数:criterion
character variable describing what criterion is to be used to test for convergence.  The possibilities are listed in .min.criterion.VGAM, but most family functions only implement a few of these.  
字符变量描述被用来测试收敛准则是什么。列出了几种可能在.min.criterion.VGAM,但大多数家庭功能只实现了其中的一些。


参数:epsilon
positive convergence tolerance epsilon. Roughly speaking, the Newton-Raphson/Fisher-scoring/local-scoring iterations are assumed to have converged when two successive criterion values are within epsilon of each other.  
积极收敛性小量。大体来说,Newton-Raphson/Fisher-scoring/local-scoring的迭代就被认为融合时,两个连续的criterion值在epsilon彼此。


参数:maxit
maximum number of Newton-Raphson/Fisher-scoring/local-scoring iterations allowed.  
最大数迭代的Newton-Raphson/Fisher-scoring/local-scoring。


参数:na.action
how to handle missing values. Unlike the SPLUS gam function, vgam cannot handle NAs when smoothing.  
如何处理缺失值。不同的是S-PLUS gam功能,vgam无法处理NA的平滑。


参数:nk
vector of length d containing positive integers. where d be the number of s terms in the formula.  Recycling is used if necessary.  The ith value is the number of B-spline coefficients to be estimated for each component function of the ith  s() term. nk differs from the number of knots by some constant. If specified, nk overrides the automatic knot selection procedure.  
的矢量长度d含有正整数。其中d是s公式中的数量。如有必要则使用回收。 i个值是B-样条系数估计每个组件的功能的i个s()术语的数目。 nk不同于一些不变的节点数。如果指定,nk覆盖自动打结选择的过程。


参数:save.weight
logical indicating whether the weights slot of a "vglm" object will be saved on the object. If not, it will be reconstructed when needed, e.g., summary.  
逻辑是否weights插槽的"vglm"对象将被保存的对象。如果没有,它会被重建需要的时候,例如,summary。


参数:se.fit
logical indicating whether approximate pointwise standard errors are to be saved on the object. If TRUE, then these can be plotted with plot(..., se = TRUE).  
逻辑是否近似的逐点的标准误差要保存的对象。如果TRUE,那么这些可以绘制出plot(..., se = TRUE)。


参数:trace
logical indicating if output should be produced for each iteration.  
逻辑表明,如果输出应为每个迭代。


参数:wzepsilon
Small positive number used to test whether the diagonals of the working weight matrices are sufficiently positive.  
小的正数,用来测试工作的权重矩阵的对角线是否有足够的积极。


参数:...
other parameters that may be picked up from control functions that are specific to the VGAM family function.   
从特定的VGAM家庭功能的控制功能,其他参数可以拿起。


Details

详细信息----------Details----------

Most of the control parameters are used within vgam.fit and you will have to look at that to understand the full details.  Many of the control parameters are used in a similar manner by vglm.fit (vglm) because the algorithm (IRLS) is very similar.
大多数的控制参数内使用vgam.fit,你必须了解的全部细节。许多控制参数以类似的方式使用由vglm.fit(vglm),因为该算法(IRLS)是非常相似的。

Setting save.weight=FALSE is useful for some models because the weights slot of the object is often the largest and so less memory is used to store the object. However, for some VGAM family function, it is necessary to set save.weight=TRUE because the weights slot cannot be reconstructed later.
设置save.weight=FALSE是weights插槽的对象是有些机型有用,因为往往是最大的,所以较少的内存用于存储该对象。然而,对于一些VGAM家庭功能,这是必要的设置save.weight=TRUE因为weights插槽不能重建。


值----------Value----------

A list with components matching the input names. A little error checking is done, but not much.  The list is assigned to the control slot of vgam objects.
组件的列表匹配输入的名字。一个小的错误进行检查,但数量不多。该列表被分配到control插槽vgam对象。


注意----------Note----------

vgam does not implement half-stepsizing, therefore parametric models should be fitted with vglm. Also, vgam is slower than  vglm too.
“”vgam没有实现半,stepsizing的,因此,参数化模型应配备vglm。此外,vgam是不是vglm太慢。


(作者)----------Author(s)----------


Thomas W. Yee



参考文献----------References----------

Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481&ndash;493.

参见----------See Also----------

vgam, vglm.control, vsmooth.spline, vglm.
vgam,vglm.control,vsmooth.spline,vglm。


实例----------Examples----------


pneumo = transform(pneumo, let = log(exposure.time))
vgam(cbind(normal, mild, severe) ~ s(let, df = 2), multinomial,
     data = pneumo, trace = TRUE, eps = 1e-4, maxit = 10)

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


注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
注2:由于是机器人自动翻译,难免有不准确之处,使用时仔细对照中、英文内容进行反复理解,可以帮助R语言的学习。
注3:如遇到不准确之处,请在本贴的后面进行回帖,我们会逐渐进行修订。
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