map.latent(SpatialExtremes)
map.latent()所属R语言包：SpatialExtremes
Two dimensional map from a Bayesian hierarchical model
从贝叶斯层次模型的二维图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function plots 2D maps from a Markov chain.
此函数图2D图，从一个马尔可夫链。
用法----------Usage----------
map.latent(fitted, x, y, covariates = NULL, param = "quant", ret.per =
100, col = terrain.colors(64), plot.contour = TRUE, fun = mean, level =
0.95, show.data = TRUE, control = list(nlines = 500), ...)
参数----------Arguments----------
参数：fitted
An object of class "latent". Typically this will be the output of latent.
对象类“潜伏”。通常情况下，这将是输出latent。
参数：x,y
Numeric vector specifying the coordinates of the grid points.
数值向量指定的网格点的坐标。
参数：covariates
An array specifying the covariates at each grid point defined by x and y. If NULL, no covariate is needed.
一个数组，指定的协变量，在每个格点x和y。如果NULL，没有协变量是必要的。
参数：param
A character string. Must be one of "loc", "scale", "shape" or "quant" for a map of the location, scale, shape parameters or for a map of a specified quantile.
一个字符串。必须有一个“禄”，“规模化”，“形”或“定量”的位置，规模，形状参数或指定的位数图的图。
参数：ret.per
A numeric giving the return period for which the quantile map is plotted. It is only required if param = "quant".
一个数字的位数图绘制的回报期。如果只需要param = "quant"。
参数：col
A list of colors such as that generated by 'rainbow', 'heat.colors', 'topo.colors', 'terrain.colors' or similar functions.
列表的颜色，如所产生的“彩虹”，“heat.colors”，“topo.colors”，“terrain.colors”或类似的功能。
参数：plot.contour
Logical. If TRUE (default), contour lines are added to the plot.
逻辑。如果TRUE（默认），等高线的图。
参数：fun
A character string specifying the function to be used to get posterior point estimates. The default is to take posterior means.
一个字符串，指定要使用的函数，得到后点估计的。的默认是，采取后路手段。
参数：level
A numeric specifying the significance level for the pointwise credible intervals.
一个数字，指定的逐点置信区间的显着性水平。
参数：show.data
Logical. Should the locations where have observed the process have to be plotted?
逻辑。的地方观察的过程要绘制的呢？
参数：control
A list with named components specifying options to be passed to rgp. Typically one might want specify nlines to reduce the computational demand.
命名的组件列表，指定要传递给rgp。通常情况下，我们可能需要指定nlines，以减少计算量。
参数：...
Several arguments to be passed to the image function.
到传递给image功能的几个参数。
值----------Value----------
A plot and a invisible list containing all the data required to do the plot.
图和一个无形的列表，其中包含所有所需的数据做的图。
（作者）----------Author(s)----------
Mathieu Ribatet
参见----------See Also----------
condrgp, map
condrgp，map
实例----------Examples----------
## Not run: [＃不运行：]
## Generate realizations from the model[＃从模型生成实现]
n.site <- 30
n.obs <- 50
coord <- cbind(lon = runif(n.site, -10, 10), lat = runif(n.site, -10 , 10))
gp.loc <- rgp(1, coord, "powexp", sill = 4, range = 20, smooth = 1)
gp.scale <- rgp(1, coord, "powexp", sill = 0.4, range = 5, smooth = 1)
gp.shape <- rgp(1, coord, "powexp", sill = 0.01, range = 10, smooth = 1)
locs <- 26 + 0.5 * coord[,"lon"] + gp.loc
scales <- 10 + 0.2 * coord[,"lat"] + gp.scale
shapes <- 0.15 + gp.shape
data <- matrix(NA, n.obs, n.site)
for (i in 1:n.site)
data[,i] <- rgev(n.obs, locs[i], scales[i], shapes[i])
loc.form <- y ~ lon
scale.form <- y ~ lat
shape.form <- y ~ 1
hyper <- list()
hyper$sills <- list(loc = c(1,8), scale = c(1,1), shape = c(1,0.02))
hyper$ranges <- list(loc = c(2,20), scale = c(1,5), shape = c(1, 10))
hyper$smooths <- list(loc = c(1,1/3), scale = c(1,1/3), shape = c(1, 1/3))
hyper$betaMeans <- list(loc = rep(0, 2), scale = c(9, 0), shape = 0)
hyper$betaIcov <- list(loc = solve(diag(c(400, 100))),
scale = solve(diag(c(400, 100))),
shape = solve(diag(c(10), 1, 1)))
## We will use an exponential covariance function so the jump sizes for[＃我们将使用指数的协方差函数，所以跳的大小为]
## the shape parameter of the covariance function are null.[＃协方差函数的形状参数是空的。]
prop <- list(gev = c(2.5, 1.5, 0.2), ranges = c(0.7, 0.75, 0.9), smooths = c(0,0,0))
start <- list(sills = c(4, .36, 0.009), ranges = c(24, 17, 16), smooths
= c(1, 1, 1), beta = list(loc = c(26, 0.5), scale = c(10, 0.2),
shape = c(0.15)))
## Generate a Markov chain[＃生成马尔可夫链]
mc <- latent(data, coord, loc.form = loc.form, scale.form = scale.form,
shape.form = shape.form, hyper = hyper, prop = prop, start = start,
n = 100)
x.grid <- y.grid <- seq(-10, 10, length = 50)
map.latent(mc, x.grid, y.grid, param = "shape")
## End(Not run)[＃（不执行）]
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 12:43:47
