corRatio(nlme)
corRatio()所属R语言包：nlme
Rational Quadratic Correlation Structure
有理二次相关结构
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function is a constructor for the corRatio class, representing a rational quadratic spatial correlation structure. Letting d denote the range and n denote the nugget effect, the correlation between two observations a distance r apart is 1/(1+(r/d)^2) when no nugget effect is present and (1-n)/(1+(r/d)^2) when a nugget effect is assumed. Objects created using this constructor need to be later initialized using the appropriate Initialize method.
此功能一个corRatio类较合理的二次空间相关结构，构造。让d表示的范围和n表示金块效果，两个观测值之间的相关距离r除了1/(1+(r/d)^2)时没有块效应是当前和(1-n)/(1+(r/d)^2) 当金块效果假设。使用此构造函数创建的对象需要初始化后使用适当Initialize方法。
用法----------Usage----------
corRatio(value, form, nugget, metric, fixed)
参数----------Arguments----------
参数：value
an optional vector with the parameter values in constrained form. If nugget is FALSE, value can have only one element, corresponding to the "range" of the rational quadratic correlation structure, which must be greater than zero. If nugget is TRUE, meaning that a nugget effect is present, value can contain one or two elements, the first being the "range" and the second the "nugget effect" (one minus the correlation between two observations taken arbitrarily close together); the first must be greater than zero and the second must be between zero and one. Defaults to numeric(0), which results in a range of 90% of the minimum distance and a nugget effect of 0.1 being assigned to the parameters when object is initialized.
可选向量与约束形式的参数值。如果nugget是FALSE，value可以只有一个元素，相应的合理的二次相关的结构，它必须是大于零的“范围”。如果nugget，是TRUE，这意味着，金块效果是目前value可以包含一个或两个元素，首先是“范围”和第二个“块效应” （一减采取任意并拢的两个观测值之间的相关性）;首先必须大于零，第二必须是0和1之间。默认numeric(0)，从而导致一系列的最小距离和90％的块金效应，被分配到的参数时object初始化0.1。
参数：form
a one sided formula of the form ~ S1+...+Sp, or ~ S1+...+Sp | g, specifying spatial covariates S1 through Sp and, optionally, a grouping factor g. When a grouping factor is present in form, the correlation structure is assumed to apply only to observations within the same grouping level; observations with different grouping levels are assumed to be uncorrelated. Defaults to ~ 1, which corresponds to using the order of the observations in the data as a covariate, and no groups.
一个片面的形式公式~ S1+...+Sp或~ S1+...+Sp | g，指定空间变项S1Sp“，可以选择，分组因子g。当一个分组的因素是在form目前，相关结构假设只适用于在同一分组级别的观察，观察不同的分组级别被假定为不相关。默认~ 1，这相当于使用秩序的意见作为协变量的数据，并没有组。
参数：nugget
an optional logical value indicating whether a nugget effect is present. Defaults to FALSE.
一个可选的逻辑值，指明是否金块效果是目前。 FALSE默认。
参数：metric
an optional character string specifying the distance metric to be used. The currently available options are "euclidean" for the root sum-of-squares of distances; "maximum" for the maximum difference; and "manhattan" for the sum of the absolute differences. Partial matching of arguments is used, so only the first three characters need to be provided. Defaults to "euclidean".
一个可选的字符串指定要使用的距离度量。目前可用的选项"euclidean"的距离平方和的根;"maximum"最大的区别;"manhattan"绝对差异的总和。部分参数的匹配使用，所以只有前三个字符需要提供。 "euclidean"默认。
参数：fixed
an optional logical value indicating whether the coefficients should be allowed to vary in the optimization, or kept fixed at their initial value. Defaults to FALSE, in which case the coefficients are allowed to vary.
一个可选的逻辑值，指明系数是否应允许不同的优化，或保持固定在其初始值。默认FALSE，在这种情况下，系数允许不同。
值----------Value----------
an object of class corRatio, also inheriting from class corSpatial, representing a rational quadratic spatial correlation structure.
corRatio类corSpatial较合理的二次空间相关结构，也从继承类的对象。
作者（S）----------Author(s)----------
Jose Pinheiro and Douglas Bates <a href="mailto:bates@stat.wisc.edu">bates@stat.wisc.edu</a>
参考文献----------References----------
S-plus", 2nd Edition, Springer-Verlag.
Models", SAS Institute.
in S and S-PLUS", Springer.
参见----------See Also----------
Initialize.corStruct, summary.corStruct, dist
Initialize.corStruct，summary.corStruct，dist
举例----------Examples----------
sp1 <- corRatio(form = ~ x + y + z)
# example lme(..., corRatio ...)[例如伦敦金属交易所（...，corRatio ...）]
# Pinheiro and Bates, pp. 222-249[皮涅伊罗和贝茨，第222-249]
fm1BW.lme <- lme(weight ~ Time * Diet, BodyWeight,
random = ~ Time)
# p. 223[页。 223]
fm2BW.lme <- update(fm1BW.lme, weights = varPower())
# p 246 [第246页]
fm3BW.lme <- update(fm2BW.lme,
correlation = corExp(form = ~ Time))
# p. 249[页。 249]
fm5BW.lme <- update(fm3BW.lme, correlation =
corRatio(form = ~ Time))
# example gls(..., corRatio ...)[例如GLS（...，corRatio ...）]
# Pinheiro and Bates, pp. 261, 263[皮涅伊罗和贝茨，第261页，263]
fm1Wheat2 <- gls(yield ~ variety - 1, Wheat2)
# p. 263 [页。 263]
fm3Wheat2 <- update(fm1Wheat2, corr =
corRatio(c(12.5, 0.2),
form = ~ latitude + longitude,
nugget = TRUE))
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。
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发表于 2012-2-16 17:51:31
