GenerateBootMatrix(GeneSelector)
GenerateBootMatrix()所属R语言包：GeneSelector
Altered datasets via bootstrap
通过引导改变的数据集
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Generates an object of class BootMatrix to be used for RepeatRanking.
生成一个类BootMatrix对象为RepeatRanking的。
用法----------Usage----------
GenerateBootMatrix(x, y, replicates = 50, type = c("unpaired", "paired", "onesample"), maxties = NULL, minclassize = 2, balancedclass = FALSE, balancedsample = FALSE, control)
参数----------Arguments----------
参数：x
Only needed if y is stored within an ExpressionSet.
如果y内ExpressionSet的存储只需要。
参数：y
y may be a numeric vector or a factor with at most two levels.<br> If x is an ExpressionSet, then y is a character specifying the phenotype variable in pData.<br> If type = "paired", take care that the coding is correct.
y可能是一个numeric矢量或在大多数两个级别的一个因素。<br>如果x是ExpressionSet，则y指定一个字符pData。参考型变量如果type = "paired"，照顾的编码是正确的。
参数：replicates
Number of bootstrap replicates to be generated.
引导号码复制到生成。
参数：type
One of "paired", "unpaired", "onesample", depends on the type of test to be performed, s. for example RankingTstat.
"paired", "unpaired", "onesample"，取决于进行的测试类型。为例子RankingTstat。
参数：maxties
The maximum number of ties allowed per observation. For example, maxties=2 means that no observation occurs more than maxties+1 = 3 times per bootstrap sample.
允许每观察关系的最大数量。例如，maxties=2意味着没有观察发生maxties+1 = 3每举样品倍多。
参数：minclassize
If minclassize=k for some integer k, then the number of observations in each class are grater then or equal to minclassize for each bootstrap sample.
如果minclassize=k一些整数k，然后每班意见，然后擦菜板或等于minclassize每个引导样本。
参数：balancedclass
If balancedclass=TRUE, then the proportions of the two classes are the same for each bootstrap sample. It is a shortcut for a certain value of minclasssize. May not be reasonable if class proportions are unbalanced in the original sample.
如果balancedclass=TRUE，然后两个班的比例是用于每举样品相同。它是为一定值minclasssize快捷。未必是合理的，如果类的比例是在原始样本不平衡。
参数：balancedsample
Should balanced bootstrap (s. details) be performed ?
应进行平衡引导（S.细节）？
参数：control
Further control arguments concerning the generation process of the bootstrap matrix, s. samplingcontrol.
关于进一步控制参数的引导矩阵的生成过程。 samplingcontrol。
Details
详情----------Details----------
For the case that balancedsample=TRUE, all other constraints as imposed by maxties, minclassize and so on are ignored. Balanced bootstrap (s. reference below) means that each observation occurs equally frequently (with respect to all bootstrap replications).
为balancedsample=TRUE，maxties征收的所有其他方面的限制，minclassize等被忽略的情况。均衡引导（S.参考下文）是指每个观察同样经常发生（与尊重所有引导重复）。
值----------Value----------
An object of class BootMatrix
一个对象的类BootMatrix
警告----------warning----------
If the generation process (partially) fails, try to
如果失败的生成过程（部分），尝试
注意----------Note----------
No bootstrap sample will occur more than once, i.e. each replication is unique.
没有引导样本将出现一次以上，即每个复制是独一无二的。
作者（S）----------Author(s)----------
Martin Slawski <br>
Anne-Laure Boulesteix
参考文献----------References----------
Bootstrap Methods and their Application.
参见----------See Also----------
GenerateFoldMatrix, RepeatRanking
GenerateFoldMatrix，RepeatRanking
举例----------Examples----------
## Load toy gene expression data[＃加载玩具基因表达数据]
data(toydata)
### class labels[＃＃类的标签]
yy <- toydata[1,]
### Generate Boot Matrix, maximum number of ties=3,[＃生成引导矩阵，最大数量的关系= 3，]
### minimum classize=5, 30 replications:[＃最低classize的= 5，30重复：]
boot <- GenerateBootMatrix(y = yy, maxties=3, minclassize=5, repl=30)
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 2012-2-25 19:02:02
