specpool(vegan)
specpool()所属R语言包：vegan
Extrapolated Species Richness in a Species Pool
外推一个物种库的物种丰富度
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The functions estimate the extrapolated species richness in a species pool, or the number of unobserved species. Function specpool is based on incidences in sample sites, and gives a single estimate for a collection of sample sites (matrix). Function estimateR is based on abundances (counts) on single sample site.
的功能估计推断物种丰富度的鱼种池，未观察到的物种的数量。功能specpool的发病率在采样点的基础上，样点（矩阵）的集合为一个单一的估计。功能estimateR是基于单个样本网站的丰度（计数）。
用法----------Usage----------
specpool(x, pool)
estimateR(x, ...)
specpool2vect(X, index = c("jack1","jack2", "chao", "boot","Species"))
poolaccum(x, permutations = 100, minsize = 3)
estaccumR(x, permutations = 100)
## S3 method for class 'poolaccum'
summary(object, display, alpha = 0.05, ...)
## S3 method for class 'poolaccum'
plot(x, alpha = 0.05, type = c("l","g"), ...)
参数----------Arguments----------
参数：x
Data frame or matrix with species data or the analysis result for plot function.
数据框或矩阵种数据或plot功能的分析结果。
参数：pool
A vector giving a classification for pooling the sites in the species data. If missing, all sites are pooled together.
一个向量，分类集中的物种数据的网站。如果缺少，所有的网站都聚集在一起。
参数：X, object
A specpool result object.
Aspecpool的结果对象。
参数：index
The selected index of extrapolated richness.
选定的指数，的推断丰富。
参数：permutations
Number of permutations of sampling order of sites.
站点的采样顺序的排列数。
参数：minsize
Smallest number of sampling units reported.
最小的抽样单位数。
参数：display
Indices to be displayed.
指数来显示。
参数：alpha
Level of quantiles shown. This proportion will be left outside symmetric limits.
水平位数所示。这一比例将被放置在外面对称的限制。
参数：type
Type of graph produced in xyplot.
在xyplot类型的图形。
参数：...
Other parameters (not used).
其它参数（未使用）。
Details
详细信息----------Details----------
Many species will always remain unseen or undetected in a collection of sample plots. The function uses some popular ways of estimating the number of these unseen species and adding them to the observed species richness (Palmer 1990, Colwell & Coddington 1994).
许多物种将永远是看不见的或未被发现的集合中的样本图。该函数使用一些流行的方法估计数这些看不见的种类和添加他们所观察到的物种丰富度（帕尔默1990年，科尔韦尔科丁顿1994年）。
The incidence-based estimates in specpool use the frequencies of species in a collection of sites. In the following, S_P is the extrapolated richness in a pool, S_0 is the observed number of species in the collection, a1 and a2 are the number of species occurring only in one or only in two sites in the collection, p_i is the frequency of species i, and N is the number of sites in the collection. The variants of extrapolated richness in specpool are:
的发病率估计在specpool使用频率的物种集合地点。在下面，S_P是一个游泳池，推断丰富S_0是观测到的种数的集合，a1和a2发生的物种数量或只在两个站点集合中，p_i是物种的频率i和N网站收集的数量。变种的推断丰富的specpool是：
The abundance-based estimates in estimateR use counts (frequencies) of species in a single site. If called for a matrix or data frame, the function will give separate estimates for each site. The two variants of extrapolated richness in estimateR are Chao (unbiased variant) and ACE. In the Chao estimate a_i refers to number of species with abundance i instead of incidence:
estimateR使用计数（频率）的物种在一个单一的网站中的丰度为基础的估计。如果矩阵或数据框，该函数将给予单独的估计，为每个站点。推断丰富estimateR是超（公正的变体）和ACE的两个变种。在超估计a_i的物种数量丰富i，而不是发病率是指：
Here a_i refers to number of species with abundance i and S_rare is the number of rare species, S_abund is the number of abundant species, with an arbitrary threshold of abundance 10 for rare species, and N_rare is the number of individuals in rare species.
这是a_i指的物种数量丰富iS_rare是珍稀物种的数量，S_abund是丰富的物种的数量，任意的阈值的丰度10对稀有物种，和N_rare是珍稀物种的个体数量。
Functions estimate the standard errors of the estimates. These only concern the number of added species, and assume that there is no variance in the observed richness. The equations of standard errors are too complicated to be reproduced in this help page, but they can be studied in the R source code of the function. The standard error are based on the following sources: Chao (1987) for the Chao estimate and Smith and van Belle (1984) for the first-order Jackknife and the bootstrap (second-order jackknife is still missing). The variance estimator of S_ace was developed by Bob O'Hara (unpublished).
函数估计的标准误差的估计。这些只关注增加物种的数量，并假设有没有差异所观察到的丰富。复制此帮助页中的标准误差的公式太复杂了，但他们可以研究在R源代码的功能。标准的错误是基于以下来源：潮（1987）超估计，史密斯和面包车的百丽（1984）的一阶刀切和自举（二阶折刀人仍下落不明）。 S_ace的方差估计是由鲍勃·奥哈拉（未出版）。
Functions poolaccum and estaccumR are similar to specaccum, but estimate extrapolated richness indices of specpool or estimateR in addition to number of species for random ordering of sampling units. Function specpool uses presence data and estaccumR count data. The functions share summary and plot methods. The summary returns quantile envelopes of permutations corresponding the given level of alpha and standard deviation of permutations for each sample size. The plot function shows the mean and envelope of permutations with given alpha for models. The selection of models can be restricted and order changes using the display argument in summary or plot. For configuration of plot command, see xyplot
功能poolaccum和estaccumR是类似specaccum，但估计specpool或estimateR除了种数的推算丰富度指数随机排序抽样单位。函数specpool使用存在的数据和estaccumR的计数数据。功能份额summary和plot方法。 summary返回位数alpha和用于每个样品大小排列的标准偏差对应的给定电平的排列信封。 plot函数的均值和包络线的排列alpha的模型。模型的选择受到限制，为了display使用summary或plot参数的变化。 plot命令的配置，请参阅xyplot
值----------Value----------
Function specpool returns a data frame with entries for observed richness and each of the indices for each class in pool vector. The utility function specpool2vect maps the pooled values into a vector giving the value of selected index for each original site. Function estimateR returns the estimates and their standard errors for each site. Functions poolaccum and estimateR return matrices of permutation results for each richness estimator, the vector of sample sizes and a table of means of permutations for each estimator.
功能specpool返回一个数据框的条目观察到的丰富和各指标中的每个类pool矢量。的效用函数specpool2vect汇总值映射到一个向量赠送价值index每个原始网站。功能estimateR返回的估计及其标准误差为每个站点。功能poolaccum和estimateR的回报矩阵置换为每个丰富估算的结果，样品大小和矢量means表排列每个估计。
注意----------Note----------
The functions are based on assumption that there is a species pool: The community is closed so that there is a fixed pool size S_P. Such cases may exist, although I have not seen them yet. All indices are biased for open communities.
该功能是基于假设有一个物种池：该社区被关闭，以便有一个固定的池大小S_P。这种情况可能存在，虽然我还没有见到它们。所有的指数都偏向开放的社区。
See http://viceroy.eeb.uconn.edu/EstimateS for a more complete (and positive) discussion and alternative software for some platforms.
一个更完整的和积极的讨论和一些平台的替代软件，请参阅http://viceroy.eeb.uconn.edu/EstimateS。
（作者）----------Author(s)----------
Bob O'Hara (<code>estimateR</code>) and Jari Oksanen.
参考文献----------References----------
data with unequal catchability. Biometrics 43, 783–791.
biodiversity through extrapolation. Phil. Trans. Roy. Soc. London B 345, 101–118.
extrapolation. Ecology 71, 1195–1198.
species richness. Biometrics 40, 119–129.
参见----------See Also----------
veiledspec, diversity, beals,
veiledspec，diversity，beals，
实例----------Examples----------
data(dune)
data(dune.env)
attach(dune.env)
pool <- specpool(dune, Management)
pool
op <- par(mfrow=c(1,2))
boxplot(specnumber(dune) ~ Management, col="hotpink", border="cyan3",
notch=TRUE)
boxplot(specnumber(dune)/specpool2vect(pool) ~ Management, col="hotpink",
border="cyan3", notch=TRUE)
par(op)
data(BCI)
## Accumulation model[＃成藏模式]
pool <- poolaccum(BCI)
summary(pool, display = "chao")
plot(pool)
## Quantitative model[＃定量模型]
estimateR(BCI[1:5,])
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 2012-10-1 15:13:41
