pdTens(mgcv)
pdTens()所属R语言包：mgcv
Functions implementing a pdMat class for tensor product smooths
实施了张量积pdMat类的功能平滑
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This set of functions implements an nlme library pdMat class to allow tensor product smooths to be estimated by lme as called by gamm. Tensor product smooths have a penalty matrix made up of a weighted sum of penalty matrices, where the weights are the smoothing parameters. In the mixed model formulation the penalty matrix is the inverse of the covariance matrix for the random effects of a term, and the smoothing parameters (times a half) are variance parameters to be estimated. It's not possible to transform the problem to make the required random effects covariance matrix look like one of the standard pdMat classes: hence the need for the pdTens class. A notLog2 parameterization ensures that the parameters are positive.
这套功能实现nlme图书馆pdMat张产品类，允许平滑估计lmegamm的叫。张量积平滑罚款矩阵的罚款矩阵，重量是平滑参数的加权总和。在混合模式制定的罚则矩阵是一个长期的随机效应的协方差矩阵的逆，平滑参数（倍半）方差参数估计。这是不可能的改造问题，使所需的随机效应的协方差矩阵的外观像一个标准的pdMat类：因此需要pdTens类。一个notLog2参数，确保参数是积极的。
These functions (pdTens, pdConstruct.pdTens, pdFactor.pdTens, pdMatrix.pdTens, coef.pdTens and summary.pdTens) would not normally be called directly.
这些功能（pdTens，pdConstruct.pdTens，pdFactor.pdTens，pdMatrix.pdTens，coef.pdTens和summary.pdTens）不会通常可直接调用。
用法----------Usage----------
pdTens(value = numeric(0), form = NULL,
nam = NULL, data = sys.frame(sys.parent()))
参数----------Arguments----------
参数：value
Initialization values for parameters. Not normally used.
初始化参数值。不能正常使用。
参数：form
A one sided formula specifying the random effects structure. The formula should have an attribute S which is a list of the penalty matrices the weighted sum of which gives the inverse of the covariance matrix for these random effects.
一个双面公式指定随机效应结构。公式应该有一个属性S这是一个罚款矩阵的加权总和，使这些随机效应的协方差矩阵的逆。
参数：nam
a names argument, not normally used with this class.
地名的说法，而不是通常使用这个类。
参数：data
data frame in which to evaluate formula.
数据框在其中计算公式。
Details
详情----------Details----------
If using this class directly note that it is worthwhile scaling the S matrices to be of "moderate size", for example by dividing each matrix by its largest singular value: this avoids problems with lme defaults (smooth.construct.tensor.smooth.spec does this automatically).
如果使用这个类直接请注意，这是值得缩放S矩阵是“大小适中”，例如，其最大的奇异值除以每个矩阵：这避免了lme违约问题（ smooth.construct.tensor.smooth.spec自动执行此操作）。
This appears to be the minimum set of functions required to implement a new pdMat class.
这似乎是一套至少需要实现一个新的pdMat类的功能。
Note that while the pdFactor and pdMatrix functions return the inverse of the scaled random effect covariance matrix or its factor, the pdConstruct function is sometimes initialised with estimates of the scaled covariance matrix, and sometimes intialized with its inverse.
请注意，而pdFactor和pdMatrix函数返回逆规模的随机效应的协方差矩阵或它的因子，pdConstruct功能有时被初始化规模的协方差矩阵的估计，有时其逆intialized用。
值----------Value----------
A class pdTens object, or its coefficients or the matrix it represents or the factor of that matrix. pdFactor returns the factor as a vector (packed column-wise) (pdMatrix always returns a matrix).
A类pdTens对象，其系数矩阵它代表该矩阵的因素。 pdFactor返回作为向量（填料塔明智）（pdMatrix总是返回一个矩阵）的因素。
作者（S）----------Author(s)----------
Simon N. Wood <a href="mailto:simon.wood@r-project.org">simon.wood@r-project.org</a>
参考文献----------References----------
参见----------See Also----------
te gamm
tegamm
举例----------Examples----------
# see gamm[看到GAMM]
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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发表于 2012-2-16 17:48:42
