spseg(seg)
spseg()所属R语言包：seg
Calculate Spatial Segregation Measures
计算空间的隔离措施
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculate Reardon and O'Sullivan's four spatial segregation measures.
计算里尔登和奥沙利文的空间隔离措施。
用法----------Usage----------
spseg(x, data, method = "all", smoothing = "none", nrow = 100,
ncol = 100, window, sigma, useC = TRUE, negative.rm = FALSE,
tol = .Machine$double.eps, verbose = FALSE, ...)
SegSpatial(env, method = "all", useC = TRUE, negative.rm = FALSE,
tol = .Machine$double.eps)
参数----------Arguments----------
参数：x
a numeric matrix or data frame with coordinates (each row is a point), or an object of class Spatial or ppp.
坐标（每行是一个点）的数字矩阵或数据框，或一个类的对象Spatial或ppp。
参数：env
an object of class SegLocalEnv.
对象类SegLocalEnv。
参数：data
an object of class matrix, or one that can be coerced to that class. The number of rows in "data" should equal the number of points in "x", and the number of columns should be greater than one (at least two population groups are required). This can be missing if "x" has a data frame attached to it.
类matrix，或可以强制转换为该类的对象。在数据的行数应等于中的“x”的点的数量，和列的数目应该大于1（需要至少两个群体）。这可能会丢失，如果x具有连接到它的数据框。
参数：method
a vector of character strings indicating an measure or measures to be computed. This must be one or more of the strings "all" (default), "exposure", "information", "diversity", and "dissimilarity". Abbreviations are accepted, as long as it is clear which method is meant.
的字符串，表示要计算一个措施或措施的向量。这必须是一个或多个字符串“所有”（默认），“曝光”，“信息化”，“多元化”和“差异性”。缩略语被接受，只要它是明确的是哪个方法。
参数：smoothing
a character string indicating a smoothing method. This must be (an abbreviation of) one of the strings "none" (default), "kernel", or "equal".
一个字符串，表示平滑的方法。这必须是（缩写）的字符串“无”（默认），“内核”，或“等于”之一。
参数：nrow
an optional numeric value indicating the number of row cells in the rasterised data surface. Ignored if "smoothing = "none"".
一个可选的数字值，该值指示在所rasterised的数据表面的行单元的数目。如果忽略“平滑”没有“。
参数：ncol
an optional numeric value indicating the number of column cells.
一个可选的数字值，该值指示列单元格的数量。
参数：window
an optional object of class owin to be passed to smooth.ppp. See "Details".
一个可选的类的对象owin：要传递给smooth.ppp。请参阅“详细信息”。
参数：sigma
an optional numeric value specifying standard deviation of isotropic Gaussian smoothing kernel to be passed to density.ppp. See also "Details".
一个可选的数字值，指定要传递给density.ppp标准差的高斯平滑核。另请参阅“详细信息”。
参数：useC
logical. If TRUE, calculate the segregation values in C.
逻辑。如果是TRUE，C.计算的隔离值
参数：negative.rm
logical. If TRUE, all geographic units where at least one group (i.e., column) has a population of zero or less will be removed to prevent -Inf or NaN in the information theory index. If FALSE, the non-positive values will be replaced with "tol".
逻辑。如果是TRUE，所有的GEO单元，其中至少有一个组（即列）零个或更少的人口将被删除，以防止INF或NaN，在信息理论指标。如果为FALSE，非正面的价值观将被替换为“托尔”。
参数：tol
the tolerance for detecting differences between values. Differences in the input values that are smaller than "tol" should make no changes in the output index values. The default is .Machine$double.eps. See help(.Machine) for definition.
公差的检测值之间的差异。不同的输入值小于托尔产出指数值没有变化。默认的.Machine$double.eps。见help(.Machine)的定义。
参数：verbose
logical. If TRUE, print the current stage of the computation and time spent on each job to the screen.
逻辑。如果是TRUE，打印的当前阶段的计算和每个作业上花费的时间，在屏幕上。
参数：...
optional arguments to be passed to getLocalEnv to compute the population composition of each local environment.
可选参数传递给getLocalEnv计算人口构成的每一个地方的环境。
Details
详细信息----------Details----------
SegSpatial computes the set of spatial segregation measures proposed by Reardon and O'Sullivan.
SegSpatial计算里尔登和奥沙利文的空间隔离措施提出的。
spseg is a wrapper function, which calls SegSpatial after constructing a population density surface and its local environment parameters with user-specified options. Currently the population density surface is estimated using the rasterize function in the raster package if the population density is assumed to be uniform in each census tract, or using density.ppp in the spatstat package if the kernel density estimation is to be used. The local environment parameters are calculated based on the output surface using getSegLocalEnv.
spseg是一个包装函数，这就要求SegSpatial施工后的人口密度表面和当地的环境参数与用户指定的选项。目前的人口密度表面使用rasterize功能，如果在每个人口普查区的人口密度被认为是均匀的raster包，或使用density.ppp中spatstat的估计包，如果内核密度估计是被使用。当地的环境参数计算的输出表面使用getSegLocalEnv。
值----------Value----------
An object of class SegSpatialExt.
对象的类SegSpatialExt。
注意----------Note----------
The exposure/isolation index, P, is presented in a matrix form. The spatial exposure of group "m" to group "n" is located in the row "m" and column "n" of the matrix. The matrix is rarely symmetric in practice so the spatial exposure index should be interpreted with care.
的曝光/隔离指数，P，提出了在以矩阵形式。空间暴露组M组N位于M的行和列的矩阵N。矩阵很少是对称的，在实践中，这样的空间曝光指数应小心解释。
The spatial isolation index values are given in the diagonal cells of the matrix; cell value at (m, m) indicates the degree of spatial isolation for group "m" for example.
空间隔离指数值给定的矩阵的对角线单元;单元格的值在（m，米）表示组的“m”例如空间隔离的程度。
（作者）----------Author(s)----------
Seong-Yun Hong
参考文献----------References----------
参见----------See Also----------
getSegLocalEnv, SegSpatial-class, rasterize, density.ppp
getSegLocalEnv，SegSpatial-class，rasterize，density.ppp
实例----------Examples----------
# Create a random data set with 50 data points and 3 population groups[创建一个随机的数据集有50个数据点和3的人口群体]
xy <- matrix(runif(100), ncol = 2)
pop <- matrix(runif(150), ncol = 3)
rana <- spseg(xy, pop, smoothing = "kernel", maxdist = 0.5)
ranb <- spseg(xy, pop, smoothing = "kernel", useExp = FALSE,
power = 0, maxdist = 0.5)
print(ranb, digits = 3)
par(mfrow = c(1, 3), mar = c(0, 1, 0, 2.5))
plot(ranb, main = "")
# Auckland population data set[奥克兰的人口数据集]
data(auckpop2006)
pp <- spseg(auckpop2006, smoothing = "kernel", maxdist = 3000)
print(pp, digits = 3)
par(mfrow = c(2, 3), mar = c(1, 1, 2.5, 2.5))
plot(pp, main = names(auckpop2006))
slot(pp, "sigma")
qq <- spseg(auckpop2006, smoothing = "kernel", maxdist = 3000, sigma = 3000)
print(qq, digits = 3)
par(mfrow = c(2, 3), mar = c(1, 1, 2.5, 2.5))
plot(qq, main = names(auckpop2006))
rr <- spseg(auckpop2006, smoothing = "kernel", maxdist = 3000, sigma = 700)
print(rr, digits = 3)
par(mfrow = c(2, 3), mar = c(1, 1, 2.5, 2.5))
plot(rr, main = names(auckpop2006))
## Not run: [＃不运行：]
ee <- spseg(auckpop2006, smoothing = "equal", maxdist = 3000)
print(ee, digits = 3)
par(mfrow = c(2, 3), mar = c(1, 1, 2.5, 2.5))
plot(ee, main = names(auckpop2006))
ff <- spseg(auckpop2006, smoothing = "equal", maxdist = 100)
gg <- spseg(auckpop2006, smoothing = "kernel", nrow = 300, ncol = 300,
maxdist = 3000, verbose = TRUE)
## 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 00:25:08
