sbdiv(simboot)
sbdiv()所属R语言包：simboot
Perform simultaneous confidence intervals or adjusted p–values for the Shannon and the Simpson index.
执行同时置信区间或在Shannon和Simpson指数调整后的p值。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Function sbdiv estimates simultaneous confidence intervals for the Shannon or the Simpson index. This function provides calculation of several pre–defined contrasts for confidence intervals.Further self-defined contrast are applicable. Simultaneous resampling confidence intervals are estimated according to the Algorithm of Besag et al. (1995) using method rpht, Westfall et al. (1993) using method WYht or similar to Beran (1988) using method tsht. Further estimation of simultaneous asymptotic intervals adjusting for heterogeneous variances is provided by method asht according to Fritsch and Hsu (1999) and Rogers and Hsu (2001). However, estimation of asymptotic intervals may make no sense in data sets with replicated samples due to overdispersion.
功能sbdiv估计同时香农Simpson指数的置信区间。此功能提供了几个预定义的对比度，的信心intervals.Further自定义的对比计算是适用的。同时再采样的置信区间估计根据算法的Besag等。 （1995）的使用方法rpht，荒野等。使用方法WYht或类似的贝兰（1988）（1993）使用方法tsht。所提供的方法，进一步估计的同时渐近间隔调整为异构差异ashtFritsch和许（1999）和罗杰斯和Hsu（2001年）。然而，估计渐近间隔可能就没有任何意义的数据集，由于偏大的复制样本。
用法----------Usage----------
sbdiv(X, f, theta = c("Shannon", "Simpson"), type = c("Dunnett",
"Tukey", "Sequen", "AVE", "Changepoint", "Williams", "Marcus", "McDermott", "UmbrellaWilliams", "GrandMean"), cmat = NULL, method = c("WYht", "tsht", "rpht", "asht"), conf.level =
0.95, alternative = c("two.sided", "less", "greater"), R = 2000, base =
1, ...)
参数----------Arguments----------
参数：X
Data frame containing numerical values for counts in columns. Every column represents on species.
数据框包含数列中的数值。每一列代表的物种。
参数：f
Vector of factorial variables for treatment groups. Vector length must be equal to the length of treatment groups multiplicated with sample replications.
治疗组的因子变量的向量。向量长度必须等于治疗样品重复multiplicated的基团的长度。
参数：theta
Biodiversity index. Options are Shannon and Simpson index.
生物多样性指数。选项Shannon和Simpson指数。
参数：type
Type of comparison. Options are Dunnett, Tukey, Sequen, AVE, Changepoint, Williams, Marcus, McDermott, UmbrellaWilliams, GrandMean intervals. We tested only Dunnett and Tukey contrasts in simulations.
类型的比较。选项是：杜克，邓尼特，顺序，AVE，Changepoint的，威廉姆斯，马库斯，麦克德莫特，UmbrellaWilliams，GrandMean间隔。在模拟过程中，我们只测试的邓尼特和Tukey对比。
参数：cmat
Optional self-defined contrast matrix. In case of using this argument, the type argument is not considered.
可选的自定义对比矩阵。的情况下使用此参数，参数的类型不被考虑。
参数：method
Possible methods are simultaneous bootstrap confidence intervals: WYht, tsht, rpht and asymptotic simultaneous confidence intervals: asht. Adjusted and unadjusted p–values are estimated with method WYht and method tsht.
可能的方法是同时进行的自举置信区间：WYht，tsht，rpht和渐近同时置信区间：asht的。经调整和未经调整的p值估计与方法WYht和方法tsht。
参数：conf.level
Pre-defined overall confidence level. Default is 0.95, while two-sided inference is estimated with (1-conf.level)/2 for each side and one-sided inference is estimated with 1-conf.level for the side of interest.
预定义的整体信心水平。默认值是0.95，而双面推断，估计(1-conf.level)/2每边的和片面的推论，估计1-conf.level供方的利益。
参数：alternative
Specified type of interval. Could be "one-sided" or "two.sided".
指定类型的区间。可能是“片面的”或“two.sided的”。
参数：R
Number of bootstrap steps. Default is 2000, which is a good compromise between accuracy and computing time
的引导步骤。默认是2000，这是一个很好的精度和计算时间之间的妥协
参数：base
Control group. base = 1 uses the first group in alphabetical order.
对照组。碱基= 1使用第一组字母顺序排列。
参数：...
Further optional arguments for the internal used function boot from package boot. Most importantly, the number of Bootstrap samples can be chosen via the parameter R (default is R=2000); see ?boot for further options.
进一步的可选参数内部使用的功能boot包boot。最重要的是，bootstrap样本的数量，可以选择通过的参数R（默认是R=2000）; ?boot进行进一步的设置。
Details
详细信息----------Details----------
sbdiv is the main function for estimating the different multiplicity adjusted confidence intervals. Different methods are called from internal functions.
sbdiv的主要功能是不同的多重调整后的置信区间估计。从内部的函数调用不同的方法。
值----------Value----------
参数：conf.int
estimate: Estimated difference between groups. Estimators differ between the methods due to calculation. lower: Lower bounds of estimated intervals. upper: Upper bounds of estimated intervals.
估计：估计群体之间的差异。估计由于计算方法之间的不同。 ：下界估计的时间间隔。上：上界估计的时间间隔。
参数：p.value
adj. p: multiplicity adjusted p-values. raw p: unadjusted p-values
ADJ。检测号码：多重调整的p值。原检测号码：未经调整的p-值
参数：conf.level
Pre-specified confidence level
预先指定的置信水平
参数：alternative
Pre-specified alternative
预先指定的替代
（作者）----------Author(s)----------
Ralph Scherer
参考文献----------References----------
Multiple Testing: Examples and Methods for <code>p</code>–Value Adjustment. New York: Wiley.
Bayesian computation and stochastic systems (with discussion) . Statistical Science, 10, 3–66.
sets. Journal of the American Statistical Association, 83, 679–686.
entropies with application to dinosaur biodiversity. Biometrics, 55, 4, 1300–1305.
biodiversity. Biometrical Journal, 43, 5, 617–625.
Indices with Application to Overdispersed Multinomial Count Data http://www.biostat.uni-hannover.de/thesis.html
实例----------Examples----------
## For plots of the datasets see the help files for the data sets.[＃图的数据集的数据集请参见帮助文件。]
## First dataset[＃第一个数据集]
data(predatGM)
## structure of data[＃数据结构]
str(predatGM)
## remove block variable[＃删除块变量]
datspec_1 <- predatGM[, -1]
str(datspec_1)
## Order of factorial variable[＃阶乘的变量]
datspec_1$Variety
## argument base = 1 uses GM as control group. Not directly executable[＃参数的基础= 1，采用GM作为对照组。不直接执行]
## due to intensive computing time[＃由于密集的计算时间。]
# sbdiv(X = datspec_1[, 2:length(datspec_1)], f = datspec_1[, 1], theta =[sbdiv（X = datspec_1 [，2：长度（datspec_1）]，F = datspec_1 [，1]，θ=]
# "Shannon", type = "Dunnett", method = "WYht", conf.level = 0.95,[“香”，类型为“邓尼特”的方法=“WYht”，conf.level = 0.95，]
# alternative = "two.sided", R = 2000, base = 1)[替代=“two.sided”，R = 2000年，碱基= 1）]
## Directly executable but senseless value for boot steps R[＃直接启动步骤的可执行文件，但毫无意义的价值ŕ]
sbdiv(X = datspec_1[, 2:length(datspec_1)], f = datspec_1[, 1], theta =
"Shannon", type = "Dunnett", method = "WYht", conf.level = 0.95,
alternative = "two.sided", R = 100, base = 1)
## Second dataset[＃第二个数据集]
data(saproDipGM)
## structure[＃结构]
str(saproDipGM)
## remove block variable[＃删除块变量]
datspec_2 <- saproDipGM[, -1]
str(datspec_2)
## Order of factor variable[＃因素变量]
datspec_2$Variety
## argument base = 2 uses Ins as control group. Not directly executable[＃参数的基础= 2，它使用了插件作为对照组。不直接执行]
## due to intensive computing time[＃由于密集的计算时间。]
# sbdiv(X = datspec_2[, 2:length(datspec_2)], f = datspec_2[, 1], theta =[sbdiv（X = datspec_2 [，2：的长度（datspec_2）]，F = datspec_2 [，1]，θ=]
# "Shannon", type = "Dunnett", method = "rpht", conf.level = 0.95,[“香”，类型为“邓尼特”的方法=“rpht”，conf.level = 0.95，]
# alternative = "two.sided", R = 2000, base = 2)[另类=“two.sided”，R = 2000，基数= 2）]
## Directly executable but senseless value for boot steps R[＃直接启动步骤的可执行文件，但毫无意义的价值ŕ]
sbdiv(X = datspec_2[, 2:length(datspec_2)], f = datspec_2[, 1], theta =
"Shannon", type = "Dunnett", method = "rpht", conf.level = 0.95,
alternative = "two.sided", R = 100, base = 2)
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 2012-9-30 02:32:28
