kriging(SpatialExtremes)
kriging()所属R语言包：SpatialExtremes
Simple kriging interpolation
简单克里金插值
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function interpolates a zero mean Gaussian random field using the simple kriging predictor.
这个函数内插一个零均值高斯随机使用简单克里格法预测的领域。
用法----------Usage----------
kriging(data, data.coord, krig.coord, cov.mod = "whitmat", sill, range,
smooth, smooth2 = NULL, grid = FALSE, only.weights = FALSE)
参数----------Arguments----------
参数：data
A numeric vector or matrix. If data is a matrix then the simple kriging predictor is given for each realisation, i.e., each row of data.
一个数值向量或矩阵。如果data是一个矩阵，那么简单克里金预测，给出了每个实现，也就是每一行的data。
参数：data.coord
A numeric vector or matrix specifying the coordinates of the observed data. If data.coord is a matrix, each row must corresponds to one location.
甲数值向量或矩阵的指定的观测数据的坐标。如果data.coord是一个矩阵，每一行必须对应到一个位置。
参数：krig.coord
A numeric vector or matrix specifying the coordinates where the kriging predictor has to be computed. If krig.coord is a matrix, each row must correspond to one location.
克里格预测要计算一个数值向量或矩阵指定坐标。如果krig.coord是一个矩阵，每一行必须对应到一个位置。
参数：cov.mod
A character string specifying the covariance function family. Must be one of "whitmat", "powexp", "cauchy", "bessel" or "caugen" for the Whittle-Matern, the powered exponential, the Cauchy, the Bessel or the generalized Cauchy covariance families.
一个字符串指定的协方差函数族。必须是一个“whitmat”，“powexp”，“柯西”，“贝塞尔”或“caugen”的为的消减，Matern，动力指数，柯西，贝塞尔或广义柯西协方差家庭的。
参数：sill,range,smooth,smooth2
Numerics specifiying the sill, range, smooth and, if any, the second smooth parameters of the covariance function.
Numerics的specifiying的窗台，范围，平滑，并且，如果没有，第二平滑参数的协方差函数。
参数：grid
Logical. Does krig.coord specifies a grid?
逻辑。 krig.coord指定一个网格？
参数：only.weights
Logical. Should only the kriging weights be computed? If FALSE, the kriging predictor isn't computed.
逻辑。克里格权重计算？如果FALSE，不计算克里格预测。
值----------Value----------
A list with components
组件列表
参数：coord
The coordinates where the kriging predictor has been computed;
克里格预测已计算的坐标;
参数：krig.est
The kriging predictor estimates;
克里格法预测估计;
参数：grid
Does coord define a grid?;
coord定义一个网格？
参数：weights
A matrix giving the kriging weights: each column corresponds to one prediction location.
给克里格权重矩阵，每一列对应一个预测位置。
（作者）----------Author(s)----------
Mathieu Ribatet
参考文献----------References----------
Spatial Uncertainty Wiley Series in Probability and Statistics.
参见----------See Also----------
condrgp, rgp, covariance.
condrgp，rgp，covariance。
实例----------Examples----------
## Kriging from a single realisation[＃实现从单一的克立格法]
n.site <- 50
n.pred <- 512
x.obs <- runif(n.site, -100, 100)
x.pred <- seq(-100, 100, length = n.pred)
data <- rgp(1, x.obs, "whitmat", sill = 1, range = 10, smooth = 0.75)
krig <- kriging(data, x.obs, x.pred, "whitmat", sill = 1, range = 10,
smooth = 0.75)
plot(krig$coord, krig$krig.est, type = "l", xlab = "x", ylab =
expression(hat(Y)(x)))
points(x.obs, data, col = 2, pch = 21, bg = 2)
## Kriging from several realisations[＃克立格法的几点认识]
n.real <- 3
data <- rgp(n.real, x.obs, "whitmat", sill = 1, range = 10, smooth = 0.75)
krig <- kriging(data, x.obs, x.pred, "whitmat", sill = 1, range = 10,
smooth = 0.75)
matplot(krig$coord, t(krig$krig.est), type = "l", xlab = "x", ylab =
expression(hat(Y)(x)), lty = 1)
matpoints(x.obs, t(data), pch = 21, col = 1:n.real, bg = 1:n.real)
title("Three kriging predictors in one shot")
## Two dimensional kriging on a grid[二维克里格法在网格上]
x.obs <- matrix(runif(2 * n.site, -100, 100), ncol = 2)
x <- y <- seq(-100, 100, length = 100)
x.pred <- cbind(x, y)
data <- rgp(1, x.obs, "whitmat", sill = 1, range = 10, smooth = 0.75)
krig <- kriging(data, x.obs, x.pred, "whitmat", sill = 1, range = 10,
smooth = 0.75, grid = TRUE)
z.lim <- range(c(data, krig$krig.est))
breaks <- seq(z.lim[1], z.lim[2], length = 65)
col <- heat.colors(64)
idx <- as.numeric(cut(data, breaks))
image(x, y, krig$krig.est, col = col, breaks = breaks)
points(x.obs, bg = col[idx], pch = 21)
## Note how the background colors of the above points matches the ones[＃注意上述各点的背景色匹配的]
## returned by the image function[＃传回的图像功能]
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 12:43:00
