Hsets(multtest)
Hsets()所属R语言包：multtest
Functions for generating guessed sets of true null hypotheses in empirical Bayes resampling-based multiple hypothesis testing
产生的功能猜到套真正的零假设在经验Bayes重采样为基础的多假设检验
译者：生物统计家园网 机器人LoveR
描述----------Description----------
These functions are called internally by the main user-level function EBMTP. They are used for estimating local q-values, generating guessed sets of true null hypotheses, and applying these results to function closures defining the choice of type I error rate (FWER, gFWER, TPPFP, and FDR).
这些功能被称为国内主要用户级功能EBMTP。它们用于估算当地的Q-值，产生真正的零假设猜测套，并运用这些结果来定义类型的选择，我的错误率（FWER，gFWER，TPPFP，FDR）的功能关闭。
用法----------Usage----------
Hsets(Tn, nullmat, bw, kernel, prior, B, rawp)
ABH.h0(rawp)
G.VS(V, S = NULL, tp = TRUE, bound)
参数----------Arguments----------
参数：Tn
The vector of observed test statistics.
观察测试统计的向量。
参数：nullmat
The matrix of null test statistics obtained either through null transformation of the bootstrap distribution or by sampling from an appropriate multivariate normal distribution (when nulldist='ic'.)
空试验的统计矩阵获得通过引导分布的空转型，或由一个适当的多元正态分布抽样（当nulldist='ic'）。
参数：bw
A character string argument to density indicating the smoothing bandwidth to be used during kernel density estimation. Default is 'nrd'.
一个字符串参数density表示将在核密度估计的平滑带宽。默认为“NRD”。
参数：kernel
A character string argument to density specifying the smoothing kernel to be used. Default is 'gaussian'.
一个字符串参数density指定要使用平滑内核。默认为“高斯”。
参数：prior
Character string indicating which choice of prior probability to use for estimating local q-values (i.e., the posterior probabilities of a null hypothesis being true given the value of its corresponding test statistic). Default is 'conservative', in which case the prior is set to its most conservative value of 1, meaning that all hypotheses are assumed to belong to the set of true null hypotheses. Other options include 'ABH' for the adaptive Benjamini-Hochberg estimator of the number/proportion of true null hypotheses, and 'EBLQV' for the empirical Bayes local q-value value estimator of the number/proportion of true null hypotheses. If 'EBLQV', the estimator of the prior probability is taken to be the sum of the estimated local q-values divided by the number of tests. Relaxing the prior may result in more rejections, albeit at a cost of type I error control under certain conditions. See references.
字符串，指示用于估算当地的Q值（即空假说真正给予其相应的检验统计量的值的后验概率）先验概率的选择。默认是“保守”，在这种情况下，事先设置其值为1，最保守的，这意味着所有的假设都假定属于一套真正的零假设。其他选项包括自适应Benjamini Hochberg的估计数/真正的虚无假设比例的“陆地棉”，EBLQV经验Bayes局部Q值/真正的零假设的数量比例值估计。先验概率估计如果“EBLQV，估计数除以测试Q值的总和。放宽之前，可能会导致更多的拒绝，但在I型误差控制在一定条件下的成本。请参阅参考资料。
参数：B
The number of bootstrap iterations (i.e. how many resampled data sets) or the number of samples from the multivariate normal distribution (if nulldist='ic'). Can be reduced to increase the speed of computation, at a cost to precision. Default is 1000.
引导迭代（即多少重采样的数据集），或从多元正态分布的样本数量（如果nulldist='ic'）。可以降低成本，以精密的计算，以增加速度，。默认值是1000。
参数：rawp
A vector of raw (unadjusted) p-values obtained bootstrap-based or influence curve null distribution.
原料（未经调整）获得引导或基于曲线空分布的影响p值向量。
参数：V
A matrix of the numbers of guessed false positives for each cut-off, i.e., observed value of a test statistic, within each sample in B.
每个切断，即一个检验统计量的观测值的数字矩阵猜测误报，每个样品内，在B。
参数：S
A matrix of the numbers of guessed true positives for each cut-off, i.e., observed value of a test statistic, within each sample in B.
每个切断，即一个检验统计量的观测值的数字矩阵猜测真阳性，在每个样品中，在B。
参数：tp
Logical indicator which is TRUE if type I error rate is a tail probability error rate and FALSE is if it is an expected value error rate.
这是TRUE，如果I型错误率是一个尾概率的错误率和假的逻辑指标是，如果它是一个预期值的误差率。
参数：bound
If a tail probability error rate, the bound to be placed on function of guessed false positives and guessed true positives. For, 'fwer', equal to 0; 'gfwer', equal to 'k'; and tppfp, equal to 'q'.
如果尾部概率的错误率，绑定将放在猜到误报功能，猜真阳性。 ，fwer，等于0; gfwer，等于K; tppfp，等于“Q”。
Details
详情----------Details----------
The most important object to be returned from the function Hsets is a matrix of indicators, i.e., Bernoulli realizations of the estimated local q-values, taking the value of 1 if the hypothesis is guessed as belonging to the set of true null hypotheses and 0 otherwise (guessed true alternative). Realizations of these probabilities are generated with a call to rbinom, meaning that this function will set the RNG seed forward another B*(the number of hypotheses) places. This matrix, with rows equal to the number of hypotheses and columns the number of (bootstrap or multivariate normal) samples is used to subset the matrix of null test statistics and the vector of observed test statistics at each round of (re)sampling into samples of statistics guessed as belonging to the sets of true null and true alternative hypotheses, respectively. Using the values of the observed test statistics themselves as cut-offs, the numbers of guessed false positives and (if applicable) guessed true positives can be counted and eventually used to estimate the distribution of a type I error rate characterized by the closure returned from G.VS. Counting of guessed false positives and guessed true positives is performed in C through the function VScount.
从功能Hsets返回最重要的对象是矩阵的指标，即伯努利变卖，估计当地的Q值，以值1，如果假设是一套真正属于猜测虚无假设，否则为0（猜到真正的替代）。调用rbinom用这些可能性的实现产生，这意味着，此功能将设置RNG的种子B*（假说数）的地方。这等于假设和列的数目（引导或多元正常）样本数量与行的矩阵，用于空试验的统计和矢量观测试验统计，在每一轮（重）抽样样本的矩阵子集统计猜到属于真正的空和真正的替代假说套，分别。自己使用的观测试验统计值削减权衡，数字猜到误报（如适用）猜到可以算作真阳性，并最终用于估计我的错误率的特点是封闭，返回一个类型的分布G.VS。通过在C函数VScount计数猜到误报猜到真阳性。
值----------Value----------
For the function Hsets, a list with the following elements:
的功能Hsets，包含下列元素的列表：
参数：Hsets.mat
A matrix of numeric indicators with rows equal to the number of test (hypotheses, typically nrow(X)) and columns the number of samples of null test statistics, B. Values of one indicate hypotheses guessed as belonging to the set of true null hypotheses based on the value of their corresponding test statistic. Values of zero correspond to hypotheses guesses as belonging to the set of true alternative hypotheses.
一个矩阵与测试（假设，通常nrow(X)）和列空测试统计的样本数，B等于行的数字指标。一个值表示猜到假设属于一套真正的零假设的基础上，其相应的检验统计量的值。零值对应属于一套真正的替代假说的假设猜测。
参数：EB.h0M
The estimated proportion of true null hypotheses as determined by nonparametric density estimation. This value is the sum of the estimated local q-values divided by the total number of tests (hypotheses).
真正的零假设，估计比例确定非参数密度估计。此值除以测试总数（假设）估计本地Q值的总和。
参数：prior
The value of the prior applied to the local q-value function. If 'conservative', the prior is set to one. Otherwise, the prior is the value obtained from the estimator of the adaptive Benjamini-Hochberg procedure (if prior is 'ABH') or from density estimation (if prior is 'EBLQV').
之前应用到当地的Q-值函数的值。如果“保守”，事先设置一个。否则，之前是从估计的的自适应Benjamini Hochberg过程中获得的价值（如果prior如果“陆地棉”）或密度估计（prior是“EBLQV）。
参数：pn.out
The vector of estimated local q-values. This vector is returned in the lqv slot of objects of class EBMTP.
估计当地的Q值的向量。这个向量返回lqv类EBMTP对象的槽。
For the function ABH.h0, the estimated number of true null hypotheses using the estimator from the linear step-up adaptive Benjamini-Hochberg procedure. <br>
的功能ABH.h0，真正的零假设，估计采用线性逐步的自适应Benjamini Hochberg过程的估计数。参考
For the function G.VS, a closure which accepts as arguments the matrices of guessed false positive and true positives (if applicable) and applies the appropriate function defining the desired type I error rate.
的功能G.VS，矩阵作为参数接受封闭猜到假阳性和真阳性（如适用），并适用相应的功能，定义所需的I型错误率。
作者（S）----------Author(s)----------
Houston N. Gilbert
参考文献----------References----------
hypothesis testing with applications to genomics: New developments in R/Bioconductor package multtest. Journal of Statistical Software (submitted). Temporary URL: http://www.stat.berkeley.edu/~houston/JSSNullDistEBMTP.pdf.<br>
discovery rate in multiple testing with independent statistics. J. Behav. Educ. Statist. Vol 25: 60-83.<br>
procedures that control the false discovery rate. Biometrika. Vol. 93: 491-507.<br>
http://www.bepress.com/sagmb/vol4/iss1/art29/ <br>
Resampling-based empirical Bayes multiple testing procedures for controlling generalized tail probability and expected value error rates: Focus on the false discovery rate and simulation study. Biometrical Journal, 50(5):716-44. http://www.stat.berkeley.edu/~houston/BJMCPSupp/BJMCPSupp.html. <br>
graphical model selection with applications to biological networks. Technical report, U.C. Berkeley Division of Biostatistics Working Paper Series, April 2009. URL http://www.bepress.com/ucbbiostat/paper245. <br>
参见----------See Also----------
EBMTP, EBMTP-class, EBMTP-methods
EBMTP，EBMTP-class，EBMTP-methods
举例----------Examples----------
set.seed(99)
data<-matrix(rnorm(90),nr=9)
group<-c(rep(1,5),rep(0,5))
#EB fwer control with centered and scaled bootstrap null distribution [EB fwer控制中心和规模化的引导空分布]
#(B=100 for speed)[（二= 100的速度）]
eb.m1<-EBMTP(X=data,Y=group,alternative="less",B=100,method="common.cutoff")
print(eb.m1)
summary(eb.m1)
par(mfrow=c(2,2))
plot(eb.m1,top=9)
abh <- ABH.h0(eb.m1@rawp)
abh
eb.m2 <- EBupdate(eb.m1,prior="ABH")
eb.m2@prior
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注：
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发表于 2012-2-26 07:38:25
