cov.sp(SpatialTools)
cov.sp()所属R语言包：SpatialTools
Calculates spatial covariance
计算空间协方差
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates spatial covariance matrix of the observed responses, and possibly, the responses to be predicted. If pcoords is not provided, then only V, the covariance matrix of the observed responses will be returned. If pcoords is provided, then Vp and Vop (the covariance matrix for predicted responses and between observed and predicted responses, respectively) will also be returned.
所观察到的响应计算空间协方差矩阵，并且可能的话，要被预测的响应。 pcoords如果没有提供，那么只有V，协方差矩阵所观察到的反应将被退回。 pcoords如果，Vp和Vop（协方差矩阵预测的反应，观察和预测之间的反应，分别）也将被退回。
用法----------Usage----------
cov.sp(coords, sp.type = "exponential",
sp.par = stop("specify sp.par argument"),
error.var = 0, smoothness = 0.5, finescale.var = 0,
pcoords = NULL, D = NULL, Dp = NULL, Dop = NULL)
参数----------Arguments----------
参数：coords
A numeric matrix of size n \times d containing the observed data locations.
一个数字矩阵的大小n \times d含有观察到的数据的位置。
参数：sp.type
A character vector specifying the spatial covariance type. Valid types are currently exponential, gaussian, matern, and spherical.
指定一个字符向量空间的协方差类型。有效的类型是目前指数，高斯，matern，球形。
参数：sp.par
A vector of length 2 specifying the scale and strength of dependence of the covariance function. The first element is the variance of the underlying spatial process (also known as the hidden or latent spatial process). This value is also called the partial sill. The second element is the strength of dependence between responses.
一个向量长度为2指定的协方差函数依赖的规模和实力。第一个元素是底层的空间处理（也被称为隐藏的或潜在的空间过程）的方差。这个值也被称为偏基台。第二个元素是响应之间的依赖的力量。
参数：error.var
A non-negative number indicating the variance of the error term.
非负数，表示误差项的方差。
参数：smoothness
A positive number indicating the variance of the error term.
正数表示误差项的方差。
参数：finescale.var
A non-negative positive number indicating the finescale variability. The is also called the microscale variance
一个非负的正数表示的finescale的变异。也被称为微尺度方差
参数：pcoords
A numeric matrix of size np \times d containing the locations of the responses to be predicted.
数值矩阵的大小np \times d包含要被预测的响应的位置。
参数：D
The Euclidean distance matrix for the coords matrix. Must be of size n \times n.
coords矩阵的欧氏距离矩阵。必须是大小n \times n。
参数：Dp
The Eucliean distance matrix for the pcoords matrix. Must be of size np \times np.
pcoords矩阵的Eucliean距离矩阵。必须是大小np \times np。
参数：Dop
The Euclidean intersite distance matrix between the locations in coords and the locations in pcoords. Must be of size n \times np.
欧氏站点间的距离矩阵之间的位置在coords的位置在pcoords的。必须是大小n \times np。
Details
详细信息----------Details----------
The spatial covariance functions are parameterized in a manner consistent with the cov.spatial function in the geoR package.
的空间协方差函数的参数一致的方式cov.spatial功能geoR包。
The D, Dp, and Dop arguments are supplied to decrease the number of necessary computations needed when performing repetitive analysis or simulations. It is probably in the user's interest to not supply these arguments unless the duration of analysis is an important consideration. Note that these arguments override the information given in coords and pcoords, i.e., if dist1(coords) != D, then D is used in subsequent calculations, etc. This could create problems.
D，Dp和Dop参数进行重复分析或模拟时，提供必要的计算需要减少的数量。这可能是用户的兴趣不提供这些参数的分析，除非持续时间是一个重要的考虑因素。请注意，这些参数将覆盖所提供的资料coords和pcoords，即如果dist1（坐标）！= D，则D是用来在随后的计算等，这可能会产生问题。
值----------Value----------
Returns a list with the following elements:
返回一个列表，包含下列元素：
参数：V
The covariance matrix for the observed responses. Will be of size n \times n.
所观察到的响应的协方差矩阵。将是大小n \times n。
参数：Vp
The covariance matrix for the predicted responses. Only returned if pcoords is supplied. Will be of size np \times np.
的协方差矩阵的预测的响应。只有返回，如果pcoords提供。将是大小np \times np。
参数：Vp
The covariance matrix between the observed responses and the predicted responses. Only returned if pcoords is supplied. Will be of size n \times np.
观察到的反应和预测的响应之间的协方差矩阵。只有返回，如果pcoords提供。将是大小n \times np。
（作者）----------Author(s)----------
Joshua French
参见----------See Also----------
simple.cov.sp
simple.cov.sp
实例----------Examples----------
coords <- matrix(rnorm(30), ncol = 3)
cov.sp(coords = coords, sp.type = "exponential", sp.par = c(2, 1),
error.var = 1)
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 2012-9-30 12:52:15
