mu.varknown(SampleSizeMeans)
mu.varknown()所属R语言包：SampleSizeMeans
Bayesian sample size determination for estimating a single normal mean with known variance
贝叶斯估计一个单一的标准方差已知的均值的样本量确定
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The function mu.varknown returns the required sample size
函数mu.varknown返回所需的样本大小
用法----------Usage----------
mu.varknown(len, lambda, n0, level = 0.95)
参数----------Arguments----------
参数：len
The desired total length of the posterior credible interval for the mean
所需的总长度后可信的时间间隔的平均值
参数：lambda
The known precision (reciprocal of variance)
已知的精度（方差的倒数）
参数：n0
Prior sample size equivalent for the mean
之前的平均样本量相当于
参数：level
The desired coverage probability of the posterior credible interval (e.g., 0.95)
所需的覆盖概率后的可信区间（如0.95）
Details
详细信息----------Details----------
Assume that a sample will be collected in order to estimate the mean of a normally distributed random variable with known precision lambda (where the precision is the reciprocal of the variance). Assume that the mean is unknown, but has prior information equivalent to n0 previous observations. The function mu.varknown returns the required sample size to attain the desired length len and coverage probability level for the posterior credible interval for the unknown mean. <br><br> This function uses a fully Bayesian approach to sample size determination. Therefore, the desired coverages and lengths are only realized if the prior distributions input to the function are used for final inferences. Researchers preferring to use the data only for final inferences are encouraged
假设将被收集的样品，以便估计精度与已知的lambda（其中精度的方差的倒数）的正态分布的随机变量的平均值。假设平均是未知的，但有先验信息，相当于N0以前的意见。函数mu.varknown返回所需的样本量，以达到所需的长度len和覆盖概率后的置信区间为未知的平均水平。参考参考这个函数使用了一个完全贝叶斯方法确定样本量。因此，只有实现所需的覆盖度和长度，如果先验分布输入到函数用于最终推论。鼓励研究人员喜欢使用的数据为最终推断
值----------Value----------
The required sample size given the inputs to the function.
所需的样本量输入的功能。
注意----------Note----------
The sample size returned by this function is exact.
这个函数返回的样本量是准确的。
（作者）----------Author(s)----------
Lawrence Joseph <a href="mailto:lawrence.joseph@mcgill.ca">lawrence.joseph@mcgill.ca</a> and Patrick Belisle
参考文献----------References----------
Bayesian sample size determination for Normal means and differences between Normal means<br>
参见----------See Also----------
mu.acc, mu.alc, mu.modwoc, mu.mbl.varknown, mu.mblacc, mu.mblalc, mu.mblmodwoc, mu.freq, mudiff.varknown, mudiff.acc, mudiff.alc, mudiff.modwoc, mudiff.acc.equalvar, mudiff.alc.equalvar, mudiff.modwoc.equalvar, mudiff.mbl.varknown, mudiff.mblacc, mudiff.mblalc, mudiff.mblmodwoc, mudiff.mblacc.equalvar, mudiff.mblalc.equalvar, mudiff.mblmodwoc.equalvar, mudiff.freq
mu.acc，mu.alc，mu.modwoc，mu.mbl.varknown，mu.mblacc，mu.mblalc，mu.mblmodwoc，mu.freq，mudiff.varknown，mudiff.acc，mudiff.alc，mudiff.modwoc，mudiff.acc.equalvar，mudiff.alc.equalvar，mudiff.modwoc.equalvar，mudiff.mbl.varknown，mudiff.mblacc ，mudiff.mblalc，mudiff.mblmodwoc，mudiff.mblacc.equalvar，mudiff.mblalc.equalvar，mudiff.mblmodwoc.equalvar，mudiff.freq
实例----------Examples----------
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 21:38:43
