joincount.multi(spdep)
joincount.multi()所属R语言包：spdep
BB, BW and Jtot join count statistic for k-coloured factors
K-色因素BB，BW和Jtot的的连接数统计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A function for tallying join counts between same-colour and different colour spatial objects, where neighbour relations are defined by a weights list. Given the global counts in each colour, expected counts and variances are calculated under non-free sampling, and a z-value reported. Since multiple tests are reported, no p-values are given, allowing the user to adjust the significance level applied. Jtot is the count of all different-colour joins.
理货相同的颜色和不同的色彩空间对象，其中定义了邻居关系的权重列表之间的连接计数的功能。鉴于全球计数在每种颜色中，预期计数和方差计算下非自由采样，和z值报告。由于多个测试报告，没有p-值是给定的，允许用户调整施加的显着性水平。 Jtot是所有不同颜色的连接数。
用法----------Usage----------
joincount.multi(fx, listw, zero.policy = FALSE,
spChk = NULL, adjust.n=TRUE)
## S3 method for class 'jcmulti'
print(x, ...)
参数----------Arguments----------
参数：fx
a factor of the same length as the neighbours and weights objects in listw
相同的长度的一个因素的邻居和权重中的对象listw
参数：listw
a listw object created for example by nb2listw
例如创建一个listw对象的nb2listw
参数：zero.policy
if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
如果是TRUE分配了零的滞后值的区域，没有邻居，如果为FALSE分配NA
参数：adjust.n
default TRUE, if FALSE the number of observations is not adjusted for no-neighbour observations, if TRUE, the number of observations is adjusted consistently (up to and including spdep 0.3-28 the adjustment was inconsistent - thanks to Tomoki NAKAYA for a careful bug report)
默认为true，如果为FALSE未调整的若干意见没有邻居的意见，如果为TRUE，观测值的数量进行调整一致（到，包括spdep 0.3-28调整是不一致的 - 由于智树中屋进行了认真的bug报告）
参数：spChk
should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use get.spChkOption()
应的数据向量空间对象的名称进行核对身份完整性，TRUE，否则返回FALSE，默认为空，使用get.spChkOption()
参数：x
object to be printed
反对要打印
参数：...
arguments to be passed through for printing
通过对印刷的参数
值----------Value----------
A matrix with class jcmulti with row and column names for observed and expected counts, variance, and z-value.
一个矩阵类jcmulti观察和预计数，方差和z值的行和列名称。
注意----------Note----------
The derivation of the test (Cliff and Ord, 1981, p. 18) assumes that the weights matrix is symmetric. For inherently non-symmetric matrices, such as k-nearest neighbour matrices, listw2U() can be used to make the matrix symmetric. In non-symmetric weights matrix cases, the variance of the test statistic may be negative.
测试（摩崖石刻和条例，1981年，第18页）的推导假设的权重矩阵是对称的。对于固有的非对称矩阵，如k-最近邻矩阵，listw2U()可以用来使矩阵对称。在非对称权重矩阵的情况下，检验统计量的方差可能是负数。
（作者）----------Author(s)----------
Roger Bivand <a href="mailto:Roger.Bivand@nhh.no">Roger.Bivand@nhh.no</a>
参考文献----------References----------
<h3>See Also</h3>
实例----------Examples----------
data(oldcol)
HICRIME <- cut(COL.OLD$CRIME, breaks=c(0,35,80), labels=c("low","high"))
names(HICRIME) <- rownames(COL.OLD)
joincount.multi(HICRIME, nb2listw(COL.nb, style="B"))
## Not run: [＃不运行：]
data(hopkins)
image(1:32, 1:32, hopkins[5:36,36:5], breaks=c(-0.5, 3.5, 20),
col=c("white", "black"))
box()
hopkins.rook.nb <- cell2nb(32, 32, type="rook")
unlist(spweights.constants(nb2listw(hopkins.rook.nb, style="B")))
hopkins.queen.nb <- cell2nb(32, 32, type="queen")
hopkins.bishop.nb <- diffnb(hopkins.rook.nb, hopkins.queen.nb, verbose=FALSE)
hopkins4 <- hopkins[5:36,36:5]
hopkins4[which(hopkins4 > 3, arr.ind=TRUE)] <- 4
hopkins4.f <- factor(hopkins4)
table(hopkins4.f)
joincount.multi(hopkins4.f, nb2listw(hopkins.rook.nb, style="B"))
cat("replicates Upton & Fingleton table 3.4 (p. 166)\n")
joincount.multi(hopkins4.f, nb2listw(hopkins.bishop.nb, style="B"))
cat("replicates Upton & Fingleton table 3.6 (p. 168)\n")
joincount.multi(hopkins4.f, nb2listw(hopkins.queen.nb, style="B"))
cat("replicates Upton & Fingleton table 3.7 (p. 169)\n")
## 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 14:39:20
