mantel.correlog(vegan)
mantel.correlog()所属R语言包：vegan
Mantel Correlogram
曼特尔相关图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function mantel.correlog computes a multivariate Mantel correlogram. Proposed by Sokal (1986) and Oden and Sokal (1986), the method is also described in Legendre and Legendre (1998, pp. 736-738).
函数mantel.correlog计算多元曼特尔相关图。索卡尔（1986）和奥登和索卡尔（1986）提出的方法还介绍了在勒让德和勒让德（1998年，第736-738）。
用法----------Usage----------
mantel.correlog(D.eco, D.geo=NULL, XY=NULL, n.class=0, break.pts=NULL,
cutoff=TRUE, r.type="pearson", nperm=999, mult="holm", progressive=TRUE)
## S3 method for class 'mantel.correlog'
plot(x, alpha=0.05, ...)
参数----------Arguments----------
参数：D.eco
An ecological distance matrix, with class either dist or matrix.
一个生态的距离矩阵，与类是dist或matrix。
参数：D.geo
A geographic distance matrix, with class either dist or matrix. Provide either D.geo or XY. Default: D.geo=NULL.
的GEO距离矩阵，与类是dist或matrix。提供是D.geo或XY。默认值：D.geo=NULL。
参数：XY
A file of Cartesian geographic coordinates of the points. Default: XY=NULL.
笛卡尔的GEO坐标点的文件。默认值：XY=NULL。
参数：n.class
Number of classes. If n.class=0, the Sturges equation will be used unless break points are provided.
班数。如果n.class=0，的斯特奇斯方程将被使用，除非破发点。
参数：break.pts
Vector containing the break points of the distance distribution. Provide (n.class+1) breakpoints, that is, a list with a beginning and an ending point. Default: break.pts=NULL.
Vector，其中包含的距离分布的中断点。断点提供（n.class 1），即，与一个开始和结束点的列表。默认值：break.pts=NULL。
参数：cutoff
For the second half of the distance classes, cutoff = TRUE limits the correlogram to the distance classes that include all points. If cutoff = FALSE, the correlogram includes all distance classes.
对于下半年的距离班，cutoff = TRUE限制的相关图类，包括所有的点的距离。如果cutoff = FALSE，相关图包括所有的距离班。
参数：r.type
Type of correlation in calculation of the Mantel statistic. Default: r.type="pearson". Other choices are r.type="spearman" and r.type="kendall", as in functions cor and mantel.
类型的相关计算中的Mantel统计量。默认值：r.type="pearson"。其他的选择r.type="spearman"和r.type="kendall"，在功能cor和mantel。
参数：nperm
Number of permutations for the tests of significance. Default: nperm=999. For large data files, permutation tests are rather slow.
为显着性检验的排列数。默认值：nperm=999。对于大型数据文件，置换测试是相当缓慢的。
参数：mult
Correct P-values for multiple testing. The correction methods are "holm" (default), "hochberg", "sidak", and other methods available in the p.adjust function: "bonferroni" (best known, but not recommended because it is overly conservative), "hommel", "BH", "BY", "fdr", and "none".
正确的P的多个测试值。修正的方法是"holm"（默认），"hochberg"，"sidak"，和其他p.adjust功能的方法："bonferroni"（最有名的，但不建议因为它过于保守），"hommel"，"BH"，"BY"，"fdr"和"none"。
参数：progressive
Default: progressive=TRUE for progressive correction of multiple-testing, as described in Legendre and Legendre (1998, p. 721). Test of the first distance class: no correction; second distance class: correct for 2 simultaneous tests; distance class k: correct for k simultaneous tests. progressive=FALSE: correct all tests for n.class simultaneous tests.
默认值：progressive=TRUE逐步修正多个测试，因为在勒让德和勒让德（1998年，第721页）。测试距离第一类：没有改正;距离第二类：同步测试正确的距离k类：正确的k同步测试。 progressive=FALSE：纠正n.class同步测试的所有测试。
参数：x
Output of mantel.correlog.
输出的mantel.correlog。
参数：alpha
Significance level for the points drawn with black symbols in the correlogram. Default: alpha=0.05.
黑色符号中的相关图绘制的点的显着性水平。默认值：alpha=0.05。
参数：...
Other parameters passed from other functions.
其他参数传递等功能。
Details
详细信息----------Details----------
A correlogram is a graph in which spatial correlation values are plotted, on the ordinate, as a function of the geographic distance classes among the study sites along the abscissa. In a Mantel correlogram, a Mantel correlation (Mantel 1967) is computed between a multivariate (e.g. multi-species) distance matrix of the user's choice and a design matrix representing each of the geographic distance classes in turn. The Mantel statistic is tested through a permutational Mantel test performed by vegan's mantel function.
甲相关图是一个曲线图，在其中的空间相关性的值绘制在纵坐标上，作为沿横坐标的研究地点之间的GEO距离，类的函数。在曼特尔相关图，的曼特尔相关（曼特尔1967）计算多变量（例如，多品种）之间的距离矩阵，用户的选择和设计矩阵的GEO距离，类反过来。的的曼特尔统计通过一个permutational的vegan的mantel函数进行Mantel检验测试。
When a correction for multiple testing is applied, more permutations are necessary than in the no-correction case, to obtain significant p-values in the higher correlogram classes.
当多个测试被施加的校正，需要更多的排列是比在没有校正的情况下，在较高的相关图类，得到显着的p值。
The print.mantel.correlog function prints out the
print.mantel.correlog函数打印出
值----------Value----------
参数：mantel.res
A table with the distance classes as rows and the class indices, number of distances per class, Mantel statistics (computed using Pearson's r, Spearman's r, or Kendall's tau), and p-values as columns. A positive Mantel statistic indicates positive spatial correlation. An additional column with p-values corrected for multiple testing is added unless mult="none".
一个表的距离行和类指数类，每类的距离，的曼特尔统计数据（计算采用Pearson Spearman的R，R，或Kendall的tau），和P-值列的数目。一个积极的曼特尔统计数字表明积极的空间相关性。 p值纠正多个测试一个附加列，除非mult="none"。
参数：n.class
The n umber of distance classes.
长的数距离班。
参数：break.pts
The break points provided by the user or computed by the program.
由用户提供的，或由程序计算的中断点。
参数：mult
The name of the correction for multiple testing. No correction: mult="none".
的名称的多个测试的校正。没有修正：mult="none"。
参数：progressive
A logical (TRUE, FALSE) value indicating whether or not a progressive correction for multiple testing was requested.
一个逻辑（TRUE，FALSE）值，该值指示是否一个渐进的调整多个测试要求。
参数：n.tests
The number of distance classes for which Mantel tests have been computed and tested for significance.
其中曼特尔测试已被计算并进行显着性测试距离类的数目。
参数：call
The function call.
函数调用。
（作者）----------Author(s)----------
Pierre Legendre, Universit茅 de Montr茅al
参考文献----------References----------
edition. Elsevier Science BV, Amsterdam.
regression approach. Cancer Res. 27: 209-220.
extension of spatial correlograms to two dimensions. Syst. Zool. 35: 608-617.
processes. 29-43 in: E. Diday et al. [eds.] Data analysis and informatics, IV. North-Holland, Amsterdam.
实例----------Examples----------
# Mite data available in "vegan"[螨数据可在“素食主义者”]
data(mite)
data(mite.xy)
mite.hel <- decostand(mite, "hellinger")
# Detrend the species data by regression on the site coordinates[Detrend种网站上的坐标数据，通过回归]
mite.hel.resid <- resid(lm(as.matrix(mite.hel) ~ ., data=mite.xy))
# Compute the detrended species distance matrix[计算去趋势物种的距离矩阵]
mite.hel.D = dist(mite.hel.resid)
# Compute Mantel correlogram with cutoff, Pearson statistic[与截止，皮尔逊统计计算曼特尔相关图]
mite.correlog = mantel.correlog(mite.hel.D, XY=mite.xy, nperm=49)
summary(mite.correlog)
mite.correlog
# or: print(mite.correlog)[或打印（mite.correlog）]
# or: print.mantel.correlog(mite.correlog)[或：print.mantel.correlog（mite.correlog）]
plot(mite.correlog)
# Compute Mantel correlogram without cutoff, Spearman statistic[计算曼特尔没有截止，Spearman等级相关图统计]
mite.correlog2 = mantel.correlog(mite.hel.D, XY=mite.xy, cutoff=FALSE,
r.type="spearman", nperm=49)
summary(mite.correlog2)
mite.correlog2
plot(mite.correlog2)
# NOTE: 'nperm' argument usually needs to be larger than 49.[注：的“nperm”的说法，通常需要大于49。]
# It was set to this low value for demonstration purposes.[这样低的值设置为示范的目的。]
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。
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发表于 2012-10-1 15:07:33
