monteBSSample-class(sampSurf)
monteBSSample-class()所属R语言包：sampSurf
Class "monteBSSample"
类“monteBSSample”
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This class contains the necessary structure for doing Monte Carlo sample size experiments under bootstrap sampling.
这个类包含了必要的结构做蒙特卡洛bootstrap抽样的样本量下的实验。
类对象----------Objects from the Class----------
Objects can be created by calls of the form new("monteBSSample", ...). However, it is preferable to use the constructor method of the same name monteBSSample to minimize problems with potentially invalid objects.
可以创建对象通过调用的形式new("monteBSSample", ...)。然而，这是最好使用相同的名称monteBSSample的构造函数方法，以尽量减少潜在的无效对象的问题。
插槽----------Slots----------
degenerate: Object of class "numeric": It may happen that, especially for small n, some of the samples drawn from the population can be degenerate (all the same value). When this happens, all of the bootstrap resamples will also be degenerate, and confidence interval estimation is impossible since it is based on the distribution of the bootstrap sample means. This slot is a numeric vector with the number of degenerate samples for each sample size in the n slot of
degenerate：类的对象"numeric"：它可能发生，特别是对小n，从人口中抽取的样品可以是简并的（相同的值）。当发生这种情况时，所有自举重新采样，也可以退化，和置信区间估计是不可能的，因为它是基于自举采样装置上的分布。此插槽是一个数值向量在n插槽用于每个样品大小与简并样本数
R: Object of class "numeric": The number of
R：类的对象"numeric"：数
means: Object of class "data.frame": The data frame contains the overall bootstrap sample means for each of the mcSamples by length(n) samples drawn from the population. The overall bootstrap sample mean is defined here as the mean of the R individual (second-stage) bootstrap sample means for each case. Taking column means gives the overall mean
means类的对象"data.frame"：数据框包含了整体的引导样本指为mcSampleslength(n)样本所得出的人口。的整体引导样本均值的平均值在这里被定义为R个人（第二阶段）引导的样本均值为每一种情况下。以列的方式，给人的整体平均
lowerCIs: Object of class "data.frame": This is the lower “BCa” confidence interval endpoint for the 1-α/2 confidence level. It is calculated from the distribution of bootstrap sample means that is created in bootstrap sampling for each Monte Carlo sample and sample size,
lowerCIs：类的对象"data.frame"：这是较低的“BCA”的置信区间端点的1-α/2置信水平。其计算方法是引导是建立在bootstrap抽样的样本均值为每个蒙特卡罗样本和样本大小的分布，
upperCIs: Object of class "data.frame": This is the upper “BCa” confidence interval endpoint for the 1-α/2 confidence level. It is calculated from the distribution of bootstrap sample means that is created in bootstrap sampling for each Monte Carlo sample and sample size,
upperCIs：类的对象"data.frame"：这是上的“BCA”的置信区间端点的1-α/2置信水平。其计算方法是引导是建立在bootstrap抽样的样本均值为每个蒙特卡罗样本和样本大小的分布，
扩展----------Extends----------
Class "monteSample", directly. <br> Class "monteBSSampleOrNULL", directly.
类"monteSample"，直接。参考类"monteBSSampleOrNULL"，直接。
方法----------Methods----------
summary signature(object = "monteBSSample"): Object summary.
总结signature(object = "monteBSSample")：对象的摘要。
（作者）----------Author(s)----------
Jeffrey H. Gove
参考文献----------References----------
参见----------See Also----------
monte, montePop
monte，montePop
实例----------Examples----------
showClass("monteBSSample")
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 22:02:26
