average.fdr(OCplus)
average.fdr()所属R语言包：OCplus
Average a two-dimensional local false discovery rate
平均一个两维的本地错误发现率
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function averages two-dimensional local false discovery rates as computed by fdr2d for binned values of the first test statistic and across the values of the second test statistic. The result can easily be plotted and should be comparable to the one-dimensional fdr as provided by fdr1d, provided that the smoothing parameters were chosen suitably.
此功能平均二维fdr2d的第一个测试统计和跨第二次测试统计值的分级值计算的本地虚假发现率。结果可以很容易地绘制，应该是可比的一维FDR提供fdr1d，平滑参数选择适当。
用法----------Usage----------
average.fdr(x, breaks)
参数----------Arguments----------
参数：x
an object returned by fdr2d.
fdr2d返回的对象。
参数：breaks
breaks defining intervals into which the first test statistic is binned; by default the same values that were used by fdr2d.
符定义到其中的第一次测试的统计是分级的时间间隔，默认情况下，fdr2d使用相同的价值观。
Details
详情----------Details----------
Assuming that we have smoothed the estimate suitably and have chosen the proportion of non-dffierentially expressed genes suitably, we should get very much the same results from fdr2d as from fdr1d when we average across the logarithmized standard errors, see Examples.
假设我们有适当的平滑估计，并选择了适当的非dffierentially表示基因的比例，我们应该得到非常fdr2dfdr1d当我们平均横跨logarithmized标准误差相同的结果， ，看到的例子。
The averaging is done across the estimated values for the actual genes; this corresponds to a weighted mean of the smoothed estimates on a grid, where the weight is proportional to cell frequencies.
平均完成跨越的实际基因的估计值，这相当于一个网格上，重量是成正比的单元频率的平滑估计的加权平均。
Note that it is usuually easier to get a good match in the tails of the curves than in the center, which is okay, as this is where we want to estimate the fdr reliably.
请注意，这是usuually更容易获得良好的匹配曲线的尾巴比在中心，这是正常的，因为这是我们想要可靠地估计FDR。
值----------Value----------
A matrix with two columns tstat and fdr.local.
与tstat和fdr.local两列的矩阵。
作者（S）----------Author(s)----------
A. Ploner
参考文献----------References----------
参见----------See Also----------
fdr2d, fdr1d
fdr2d，fdr1d
举例----------Examples----------
# Create res1d[创建res1d]
example(fdr1d)
# Compute fdr2d using the p0[计算fdr2d使用的P0]
res2d = fdr2d(xdat, grp, p0=p0(res1d))
# Show it[显示它]
par(mfrow=c(2,1))
plot(res1d, main="fdr1d and averaged fdr2d")
lines(average.fdr(res2d), col="red")
plot(res2d, grid=TRUE, main="fdr2d is averaged across columns")
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 2012-2-26 08:01:11
