cov.st(SpatialTools)
cov.st()所属R语言包：SpatialTools
Calculates spatio-temporal covariance
计算时空协方差
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.st(coords, time, sp.type = "exponential",
sp.par = stop("specify sp.par argument"),
error.var = 0, smoothness = 0.5, finescale.var = 0,
t.type = "ar1", t.par = .5,
pcoords = NULL, ptime = NULL,
D = NULL, Dp = NULL, Dop = NULL,
T = NULL, Tp = NULL, Top = 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：time
A numeric matrix of size n \times 1 containing the times at which the data was observed.
一个数字矩阵的大小n \times 1包含的数据的时间。
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 dependence of the covariance function. The first element refers to the variance of the hidden process (sometimes this is called the partial sill) while the second elements determines the strength of dependence between locations.
长度为2的向量指定的规模和协方差函数的依赖。第一个元素是指隐藏进程（有时这就是所谓的偏基台）的差异，而第二个元素的位置之间的依赖关系的强弱决定了。
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：t.type
A character vector indicating the temporal dependance structure. Currently, only "ar1" is implemented.
一个字符向量说明的时间DEPENDANCE结构。目前，只有“AR1”的实施。
参数：t.par
A numeric vector of length 1 indicating the strength of temporal dependence.
一个数值向量的长度为1，表示时间依赖性的实力。
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含有要被预测的位置的响应
参数：ptime
A numeric matrix of size np \times 1 containing the times at which the responses are to be predicted.
一个数字矩阵的大小np \times 1包含时代的反应是可以预测的。
参数：D
The Euclidean distance matrix for the coords matrix. Must be of size n \times n.
欧氏距离矩阵的坐标矩阵。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.
为pcoords矩阵Eucliean距离矩阵。必须是大小np \times np。
参数：Dop
The Eucliean intersite distance matrix between the locations in coords and the locations in pcoords. Must be of size n \times np.
Eucliean站点间距离矩阵之间的位置坐标和位置pcoords。必须是大小n \times np。
参数：T
The Euclidean distance matrix for the time matrix. Must be of size n \times n.
欧氏距离矩阵的矩阵。必须是大小n \times n。
参数：Tp
The Eucliean distance matrix for the ptime matrix. Must be of size np \times np.
Eucliean距离矩阵为ptime的矩阵。必须是大小np \times np。
参数：Top
The Eucliean intertime distance matrix between the times in time and ptime. Must be of size n \times np.
Eucliean intertime距离矩阵之间的时间在time和ptime。必须是大小n \times np。
Details
详细信息----------Details----------
At this point, this function only implements a separable spatio-temporal covariance funcation. If h is the distance between two sites, and t is the temporal lag between the times when the associated responses were observed, then the covariance function C(h,t) = Cs(h) \times Ct(t) where Cs is a spatial covariance function corresponding to the exponential, matern, gaussian, or spherical and Ct is the temporal covariance function corresponding to an ar1 process with Ct(t) = φ ^ t.
在这一点上，此功能只实现了一个可分离协方差funcation时空的。如果h两个站点之间的距离，和t是相关的反应，观察的时候，那么协方差函数之间的时间延迟C(h,t) = Cs(h) \times Ct(t)其中Cs是一个空间协方差函数对应的指数，matern，高斯，或球形和Ct是对应与Ct(t) = φ ^ tAR1过程的时间的协方差函数。
The D, Dp, Dop, T, Tp, Top 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, pcoords, time, and prime, i.e., if dist1(coords) != D, then D is used in subsequent calculations, etc. This could create problems.
D，Dp，Dop，T，Tp，Top参数提供一些必要的计算，以减少需要进行重复时，分析和模拟。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，pcoords，time和prime，也就是说，如果dist1（坐标）！= D，则D是用于随后的计算等，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.
所观察到的响应的协方差矩阵。
参数：Vp
The covariance matrix for the predicted responses. Only returned if pcoords is supplied.
的协方差矩阵的预测的响应。只有返回，如果pcoords提供。
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。会不会是的大小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)
pcoords <- matrix(rnorm(90), ncol = 3)
time <- 1:10
ptime <- 1:30
cov.st(coords = coords, time = time, sp.type = "exponential",
sp.par = c(2, 1), error.var = 1, t.type = "ar1", t.par = .5,
pcoords = pcoords, ptime = ptime)
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 12:52:21
