SigDiff(SDMTools)
SigDiff()所属R语言包：SDMTools
Identify Regions of Significant Differences
确定区域的显着差异
译者：生物统计家园网 机器人LoveR
描述----------Description----------
SigDiff computes the significance of the pairwise differences relative to the mean and variance of all differences between the two input datasets. This is useful for identifying regions of significant difference between two datasets (e.g., different DEMs (Januchowski et al. 2010) or different species distribution model predictions (Bateman et al 2010)). <br> <br> ImageDiff is a wrapper to the image.asc command in adehabitat package that uses the result from SigDiff to create an image mapping the regions of significant differences (positive and negative). <br> <br> NOTE: it is assumed the input data are of the same extent and cellsize.
SigDiff计算的两两相对的两个输入数据集之间的所有差异的均值和方差的差异的意义。区识别两个数据集（例如，不同的数字高程模型（Januchowski等2010）或不同的物种分布模型的预测结果（贝特曼等2010））的显着区别，这是非常有用的。参考参考ImageDiff是一个包装的image.asc在adehabitat包使用命令的结果SigDiff创建图像映射区域的显着性差异（正面和负面的）。 <BR> <BR>注意：假定输入数据的相同程度和CELLSIZE的是。
用法----------Usage----------
SigDiff(x,y,pattern=TRUE)
ImageDiff(tasc,sig.levels=c(0.025,0.975),tcol=terrain.colors(3),...)
参数----------Arguments----------
参数：x
a vector or matrix of data; the matrix can be of can be a raster of class 'asc' (adehabitat package), 'RasterLayer' (raster package) or 'SpatialGridDataFrame' (sp package)
数据的向量或矩阵的矩阵可以是一个栅格类的递增（adehabitat包），的“RasterLayer”（栅格包）或“SpatialGridDataFrame（SP包）
参数：y
a vector or matrix of data with the same dimensions and class of 'x'
的向量或矩阵的数据具有相同的尺寸和类的x
参数：pattern
logical value defining if differences are respective to relative patterning (TRUE) or absolute values (FALSE)
逻辑值定义，如果差异是各自相对图案（TRUE）或绝对值（FALSE）
参数：tasc
a matrix of probability values (0 to 1) likely created by SigDiff; The matrix can be a raster of class 'asc' (adehabitat package), 'RasterLayer' (raster package) or 'SpatialGridDataFrame' (sp package)
概率值（0到1）的矩阵的可能创建的SigDiff;基质可以是类递增（adehabitat包），的RasterLayer（栅格包）或SpatialGridDataFrame（藻封装栅格）
参数：sig.levels
the significance levels to define significantly above and below. Default settings represent significance at the 0.05 level
显着的上面和下面定义的显着性水平。默认设置代表的显着性水平（P <0.05）
参数：tcol
a set of 3 colors for use in the image to represent significantly lower or greater, and not significant
一组的3的图像中使用的颜色来表示显着低于或更大，而不是显着的
参数：...
other graphical parameters defined by image() or plot()
其他图形参数定义的图像（）或plot（）
值----------Value----------
SigDiff returns a vector or matrix of the same dimensions and class of the input representing the significance of the pairwise difference relative to the mean and variance of all differences between the two inputs. <br> <br> ImageDiff returns nothing but creates an image of the areas of significant differences
SigDiff返回相同的尺寸和类代表意义的两两差的均值和方差的两个输入端之间的所有差异的输入向量或矩阵。参考参考ImageDiff返回只不过是创建一个图像方面的显著差异
（作者）----------Author(s)----------
Stephanie Januchowski <a href="mailto:stephierenee@gmail.com">stephierenee@gmail.com</a>
参考文献----------References----------
Bateman, B.L., VanDerWal, J., Williams, S.E. & Johnson, C.N. (2010) Inclusion of biotic interactions in species distribution models improves predictions under climate change: the northern bettong Bettongia tropica, its food resources and a competitor. Journal of Biogeography, In Review.
实例----------Examples----------
#create some simple objects of class 'asc'[创建一些简单的对象类ASC]
tasc = as.asc(matrix(1:50,nr=50,nc=50)); print(tasc)
#modify the asc objects so that they are slightly different[修改递增，让他们略有不同的对象]
tasc1 = tasc + runif(n = 2500, min = -1, max = 1)
tasc2 = tasc + rnorm(n = 2500, mean = 1, sd = 1)
#create graphical representation[创建图形表示]
par(mfrow=c(2,2),mar=c(1,1,4,1))
image(tasc1,main='first grid',axes=FALSE)
image(tasc2,main='second grid',axes=FALSE)
#get significant difference by spatial patterning[获得显着差异的空间图案]
out = SigDiff(tasc1,tasc2)
ImageDiff(out,main="Pattern Differences",axes=FALSE)
#get significant difference [获得显著差异]
out = SigDiff(tasc1,tasc2,pattern=FALSE)
ImageDiff(out,main="Absolute Differences",axes=FALSE)
legend('topleft',legend=c('-ve','ns','+ve'),title='significance',
fill=terrain.colors(3),bg='white')
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 2012-9-29 23:36:58
