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R语言 segmented包 slope()函数中文帮助文档(中英文对照)

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发表于 2012-9-30 00:23:29 | 显示全部楼层 |阅读模式
slope(segmented)
slope()所属R语言包:segmented

                                         Slope estimates from segmented relationships
                                         坡估计分割的关系

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Computes the slopes of each "segmented" relationship in the fitted model.
计算每个“分段”的关系拟合模型的山坡上。


用法----------Usage----------


slope(ogg, parm, conf.level = 0.95, rev.sgn=FALSE, var.diff=FALSE,
  APC=FALSE)



参数----------Arguments----------

参数:ogg
an object of class "segmented", returned by any segmented method.  
一个类的对象“分段”,返回的任何segmented方法。


参数:parm
the segmented variable whose slopes have to be computed. If missing all the segmented variables are considered.  
分段变量必须被计算,其斜坡。如果被认为是丢失了所有的分段变量。


参数:conf.level
the confidence level required.  
所需的置信水平。


参数:rev.sgn
vector of logicals. The length should be equal to the length of parm, but it is recycled otherwise. when TRUE it is assumed that the current parm is "minus" the actual segmented variable, therefore the sign is reversed before printing. This is useful when a null-constraint has been set on the last slope.
向量,逻辑值。长度应等于的长度parm,但它被回收,否则。当TRUE,假设当前parm是减去的实际分段变量,因此,该标志在打印前拨回。这是非常有用的,在过去的斜坡上设置了一个空的约束时。


参数:var.diff
logical. If var.diff=TRUE and there is a single segmented variable, the computed standard errors  are based on a sandwich-type formula of the covariance matrix. See Details in summary.segmented.  
逻辑。如果var.diff=TRUE和有一个单一的分段变量,计算标准误差是基于上一个三明治类型的协方差矩阵的公式。详细,在summary.segmented。


参数:APC
logical. If APC=TRUE the "annual percent changes", i.e. 100*(exp(b)-1),  are computed for each interval (b is the slope). Only point estimates and confidence intervals are returned.   
逻辑。如果APC=TRUE的年度百分比变化,即100*(exp(b)-1),计算每个区间(b是斜率)。只有点估计和区间估计被返回。


Details

详细信息----------Details----------

To fit broken-line relationships, segmented uses a parameterization whose coefficients are not  the slopes. Therefore given an object "segmented", slope computes point estimates, standard errors, t-values and confidence intervals of the slopes of each segmented relationship in the fitted model.
为了适应虚线关系,segmented使用参数化的系数是不斜坡。因此对象"segmented",slope计算点估计,标准误,t值和置信区间的拟合模型中的每一个分割的关系的斜坡。


值----------Value----------

slope returns a list of matrices. Each matrix represents a segmented relationship and its number of rows equal  to the number of segments, while five columns summarize the results.
slope返回一个列表的矩阵。每个矩阵代表一个分段的关系和其的段的数量等于行数,而五列总结了结果。


注意----------Note----------

The returned summary is based on limiting Gaussian distribution for the model parameters involved  in the computations. Sometimes, even with large sample sizes such approximations are questionable  (e.g., with small difference-in-slope parameters) and the results returned by slope  might be unreliable. Therefore is responsability of the user to gauge the applicability of such asymptotic  approximations. Anyway, the t values may be not assumed for testing purposes  and they should be used just as guidelines to assess the estimate uncertainty.
限制在计算中所涉及的模型参数的高斯分布的基础上返回的摘要。有时候,即使有大的样本量,这样的近似问题的(例如,用小的差异斜率参数),并把结果返回slope可能是不可靠的。所以对用户的责任,以了解这种渐近的适用性。总之,t值不用于测试目的的假设,他们应该只是作为指引,以评估估计的不确定性。


(作者)----------Author(s)----------


Vito M. R. Muggeo, <a href="mailto:vito.muggeo@unipa.it">vito.muggeo@unipa.it</a>




参考文献----------References----------

Statistics in Medicine 22, 3055&ndash;3071.

参见----------See Also----------

See also davies.test to test for a nonzero differece-in-slope parameter.
请参阅davies.test到一个的非零differece在斜率参数测试。


实例----------Examples----------


set.seed(16)
x<-1:100
y<-2+1.5*pmax(x-35,0)-1.5*pmax(x-70,0)+rnorm(100,0,3)
out<-glm(y~1)
out.seg<-segmented(out,seg.Z=~x,psi=list(x=c(20,80)))
## the slopes of the three segments....[#斜坡三个环节......]
slope(out.seg)
rm(x,y,out,out.seg)
#[]
## an heteroscedastic example..[#异方差的例子。]
set.seed(123)
n<-100
x<-1:n/n
y<- -x+1.5*pmax(x-.5,0)+rnorm(n,0,1)*ifelse(x<=.5,.4,.1)
o<-lm(y~x)
oseg<-segmented(o,seg.Z=~x,psi=.6)
slope(oseg)
slope(oseg,var.diff=TRUE) #better CI[更好的CI]

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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