sampleSize(SSPA)
sampleSize()所属R语言包：SSPA
Creates an object of class SampleSize
创建一个类中的采样对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function sampleSize initializes a SampleSize-object. The density of effect-sizes is estimated using a deconvolution estimator or constrained optimization using B-splines.
功能sampleSizeSampleSize对象初始化。使用卷积估计或使用B样条的约束优化的效应大小的密度估计。
用法----------Usage----------
sampleSize(PilotData, method = c("Langaas", "Storey", "Ferreira", "Ruppert", "Userdefined"), from = -6, to = 6, resolution = 2^10, kernel = c("fan", "wand", "sinc"), pi0 = seq(0.1, 0.99, 0.01), adjust=TRUE, a=0.5, nKnots = 11, bDegree = 3, ...)
参数----------Arguments----------
参数：PilotData
object of class PilotData on which the sample size and power analysis will be performed
类对象PilotData上的样本大小和功率分析将进行
参数：method
character string giving the method for estimation of the fraction of non-differentially expressed genes either one of:
字符串给非差异分数的估计方法表达基因的一方：
"Langaas" (default)
“Langaas”（默认）
"Storey"
“楼层”
"Ferreira"
“费雷拉”
"Ruppert"
“Ruppert公司”
"Userdefined" </ul>
“用户定义”</ UL>
参数：from
Lower bound of the density of effect-sizes (the range should be symmetric)
降低的密度势必影响大小（范围应该是对称的）
参数：to
Upper bound of the density of effect-sizes.
上势必影响大小的密度。
参数：resolution
the number of points on which the density of effect-sizes will be estimated (must be a power of 2)
上点密度的影响大小，将估计的数目（必须是2的乘方）
参数：kernel
the kernel type used in the deconvolution estimator either one of:
卷积估计任一个内核类型：
"fan" (default)
“粉丝”（默认）
"wand"
“魔杖”
"sinc" </ul>
“SINC”</ UL>
参数：pi0
numeric or a vector of type numeric giving the fraction of non-differentially expressed genes. If method="Userdefined" a userdefined pi0 is obligated. If method="Ferreira" a range of values should be given e.g. seq(0.01, 0.99, 0.01)
数字或矢量型数字非差异表达基因的分数。如果method="Userdefined"用户定义PI0责任。如果方法=“费雷拉”值的范围应如seq(0.01, 0.99, 0.01)
参数：adjust
is the density of effect sizes adjusted (adjust=TRUE, default) or not (adjust=FALSE)
调节的影响大小的密度（adjust=TRUE，默认）或（adjust=FALSE）
参数：a
For better upper bound estimates of pi0 as described by Efron et al. (2001).
对于更好的上限为PI0埃弗龙等人描述的估计。 （2001年）。
参数：nKnots
number of knots used in Rupperts method for estimating the proportion of non-differentially expressed genes and density of effect-sizes
在Rupperts方法用于估算非差异表达基因的影响大小和密度的比例节
参数：bDegree
degree of B-spline basis used in Rupperts method for estimating the proportion of non-differentially expressed genes and density of effect-sizes
B样条基度使用非差异表达基因的影响大小和密度的比例估计在Rupperts方法
参数：...
Additional parameters for method for the estimation of the fraction of non-differentially expressed genes (Doesn't work yet!)
额外的参数（非差异表达基因的分数估计方法还没有起作用！）
Details
详情----------Details----------
The sampleSize function performes the estimation of the proportion of non-differentially expressed genes using one of the three methods, "Langaas", "Storey", "Ferreira" if method="Userdefined" a userdefined pi0 is needed and estimation of the proportion of non-differentially expressed genes will be skipped. A deconvolution estimator is implemented using the Fast Fourier Transform Algorithm fft() for estimations of the density of effect sizes. If method="Ruppert" constrained optimization using B-splines is used, for this method two additional packages needs to be installed namely quadprog and splines. Both the proportion of non-differentially expressed genes and the density of effect sizes are estimated with Ruppert's method. In contrast to the orginal method of Ruppert et al. (2007) we made a modification on the estimation of the density of effect sizes allowing for negative effect sizes as well.
sampleSize函数performes的差异表达的基因使用的三种方法之一，"Langaas", "Storey", "Ferreira"如果method="Userdefined"用户自定义的pi0需要和估计的比例估计非差异表达基因的比例将被跳过。一个卷积估计是利用快速傅立叶变换算法fft()影响大小的密度估计。如果method="Ruppert"使用B样条的约束优化使用，这种方法需要安装两个额外的软件包，即quadprog和splines。非差异表达基因的比例和影响大小的密度估计与Ruppert公司的方法。相比之下Ruppert公司等原价方法。 （2007年），我们对负面影响的大小以及允许的效果大小的密度估计的修改。
值----------Value----------
Object of class SampleSize
对象类SampleSize
作者（S）----------Author(s)----------
Maarten van Iterson
参考文献----------References----------
Approximate Power and Sample Size Calculations with Microarray Data: An Illustration. Statistical Applications in Genetics and Molecular Biology 5, (1).
Estimating the proportion of true null hypotheses, with application to DNA microarray data. Journal of the Royal Statistical Society Series B, 67, 555-572.
A direct approach to false discovery rates. J.R. Statist. Med. 27, 1960-1972.
Exploring the information in p-values for the analysis and planning of multiple-test experiments. Biometrics, 63, 2, 483-95.
Empirical Bayes Analysis of a Microarray Experiment. Journal of the American Statistical Association, 96, 456, 1151-1160.
参见----------See Also----------
convest, qvalue and SampleSize use class?SampleSize
convestqvalue和SampleSize用class?SampleSize
举例----------Examples----------
library(multtest)
data(golub)
teststat <- mt.teststat(golub, golub.cl)
table(golub.cl)
pd <- pilotData(name="golub", testStatistics=teststat, sampleSizeA=11, sampleSizeB=27)
hist(pd)
plot(pd)
ss <- sampleSize(pd)
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。
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发表于 2012-2-26 15:07:21
