decostand(vegan)
decostand()所属R语言包:vegan
Standardization Methods for Community Ecology
生态社区的标准化方法
译者:生物统计家园网 机器人LoveR
描述----------Description----------
The function provides some popular (and effective) standardization methods for community ecologists.
该功能提供了一些流行和有效的标准化方法,为社会生态学家。
用法----------Usage----------
decostand(x, method, MARGIN, range.global, logbase = 2, na.rm=FALSE, ...)
wisconsin(x)
参数----------Arguments----------
参数:x
Community data, a matrix-like object.
社区数据,类似矩阵的目的。
参数:method
Standardization method. See Details for available options.
标准化的方法。可用选项的详细信息。
参数:MARGIN
Margin, if default is not acceptable. 1 = rows, and 2 = columns of x.
保证金,如果默认情况下是不能接受的。 1=行,和2=x。
参数:range.global
Matrix from which the range is found in method = "range". This allows using same ranges across subsets of data. The dimensions of MARGIN must match with x.
矩阵的范围内被发现在method = "range"。这允许使用相同的范围内跨越的数据的子集。 MARGIN的尺寸必须与x。
参数:logbase
The logarithm base used in method = "log".
对数的底method = "log"。
参数:na.rm
Ignore missing values in row or column standardizations.
忽略缺少的行或列中的值标准化。
参数:...
Other arguments to the function (ignored).
其他参数的功能(忽略)。
Details
详细信息----------Details----------
The function offers following standardization methods for community data:
该功能提供了社会数据的标准化方法如下:
total: divide by margin total (default MARGIN = 1).
total:除以利润率总(默认MARGIN = 1“)。
max: divide by margin maximum (default MARGIN = 2).
max:除以利润率最高(默认MARGIN = 2)。
freq: divide by margin maximum and multiply by the number of non-zero items, so that the average of non-zero entries is one (Oksanen 1983; default MARGIN = 2).
freq:除以余量最大的和乘以非零项的数目,从而使平均非零项是酮(奥克萨宁1983,预设MARGIN = 2)。
normalize: make margin sum of squares equal to one (default MARGIN = 1).
normalize:追加保证金的平方之和等于1(默认MARGIN = 1)。
range: standardize values into range 0 ... 1 (default MARGIN = 2). If all values are constant, they will be transformed to 0.
range:规范值范围为0 ... 1(默认MARGIN = 2)。如果所有的值是恒定的,它们将被转化为0。
standardize: scale x to zero mean and unit variance (default MARGIN = 2).
standardize:规模x零均值和单位方差(默认MARGIN = 2)。
pa: scale x to presence/absence scale (0/1).
pa:规模x存在/不存在规模(0/1)。
chi.square: divide by row sums and square root of column sums, and adjust for square root of matrix total (Legendre & Gallagher 2001). When used with the Euclidean distance, the distances should be similar to the Chi-square distance used in correspondence analysis. However, the results from cmdscale would still differ, since CA is a weighted ordination method (default MARGIN = 1).
chi.square:除以列和行款项和平方根,并调整为矩阵总的平方根(2001年勒让德 - 加拉格尔)。当使用欧氏距离,距离应该是相似的对应分析中使用的卡方距离。然而,cmdscale的结果仍然会有所不同,因为CA是一个加权协调的方法(默认MARGIN = 1“)。
hellinger: square root of method = "total" (Legendre & Gallagher 2001).
hellinger:method = "total"(2001年勒让德 - 加拉格尔)的平方根。
log: logarithmic transformation as suggested by Anderson et al. (2006): log_b (x) + 1 for x > 0, where b is the base of the logarithm; zeros are left as zeros. Higher bases give less weight to quantities and more to presences, and logbase = Inf gives the presence/absence scaling. Please note this is not log(x+1). Anderson et al. (2006) suggested this for their (strongly) modified Gower distance, but the standardization can be used independently of distance indices.
log:Anderson等人所建议的对数变换。 (2006年):log_b (x) + 1x > 0,其中b是对数的底数,留下零为零。较高的碱给数量和更多的存在较小的权重,和logbase = Inf给人的存在/不存在缩放。请注意,这不是log(x+1)。 Anderson等人。 (2006)建议(强)修改后的高尔距离,但距离指数的标准化可以独立使用。
Standardization, as contrasted to transformation, means that the entries are transformed relative to other entries.
标准化,对比改造的项目,这意味着相对于其他项目转化。
All methods have a default margin. MARGIN=1 means rows (sites in a normal data set) and MARGIN=2 means columns (species in a normal data set).
所有的方法都有一个默认保证金。 MARGIN=1是指行(在一个正常的数据集的网站)和MARGIN=2是指列(种在一个正常的数据集)。
Command wisconsin is a shortcut to common Wisconsin double standardization where species (MARGIN=2) are first standardized by maxima (max) and then sites (MARGIN=1) by site totals (tot).
命令wisconsin是一条捷径共同威斯康星双标准化种(MARGIN=2)是第一个标准化的最大值(max),然后网站(MARGIN=1)的网站总数( tot“)。
Most standardization methods will give nonsense results with negative data entries that normally should not occur in the community data. If there are empty sites or species (or constant with method = "range"), many standardization will change these into NaN.
大多数标准化的的方法会给废话的结果与负的数据项,通常不应该发生在社区数据。如果是空的网站或物种(或常数method = "range"),许多标准化将改变成NaN。
值----------Value----------
Returns the standardized data frame, and adds an attribute "decostand" giving the name of applied standardization "method".
返回标准化的数据框,并添加一个属性"decostand"应用标准化"method"的名称。
注意----------Note----------
Common transformations can be made with standard R functions.
常见的转换可以用标准的R功能。
(作者)----------Author(s)----------
Jari Oksanen and Etienne Lalibert茅
(<code>method = "log"</code>).
参考文献----------References----------
dispersion as a measure of beta diversity. Ecology Letters <STRONG>9</STRONG>, 683–693.
transformations for ordination of species data. Oecologia <STRONG>129</STRONG>, 271–280.
principal component analysis, correspondence analysis and multidimensional scaling. Vegetatio <STRONG>52</STRONG>, 181–189.
实例----------Examples----------
data(varespec)
sptrans <- decostand(varespec, "max")
apply(sptrans, 2, max)
sptrans <- wisconsin(varespec)
## Chi-square: PCA similar but not identical to CA.[智方:PCA相似但不相同的CA。]
## Use wcmdscale for weighted analysis and identical results.[#使用wcmdscale的加权分析和相同的结果。]
sptrans <- decostand(varespec, "chi.square")
plot(procrustes(rda(sptrans), cca(varespec)))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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