gofTest(tweeDEseq)
gofTest()所属R语言包:tweeDEseq
Test the goodness of fit of every row in a matrix of counts
在计数矩阵的每一行的拟合优度测试
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Function to test the goodness of fit of every row in a matrix of counts
功能测试中的计数矩阵的每一行的拟合优度
用法----------Usage----------
gofTest(counts, a = 0, mc.cores = 1)
参数----------Arguments----------
参数:counts
matrix of counts
计数矩阵
参数:a
numeric scalar smaller than 1. The function will test whether the shape parameter is equal to the introduced 'a' (default is 0).
数字标量小于1。该函数将测试的形状参数是否等于引进的“A”(默认为0)。
参数:mc.cores
number of cpu cores to be used. This option is only available when the 'multicore' package is installed and loaded first. In such a case, if the default value of mc.cores=1 is not changed, all available cores will be used.
要使用的CPU核心的数量。此选项仅适用于多核包安装时,首先加载。默认值mc.cores=1没有改变,在这种情况下,所有可用的内核将被使用。
Details
详情----------Details----------
By default a = 0, and therefore the function tests for every row of the input matrix of counts whether the count data follows a Negative-Binomial distribution. In this case, a Likelihood Ratio Test is performed. When the given value for 'a' is different from 0, a Wald test is performed. This function calls testShapePT.
默认情况下,= 0,因此,输入矩阵的计数,计数数据是否遵循一个负二项分布的每一行的功能测试。在这种情况下,似然比检验。当一给定值是从0不同,Wald检验。此函数调用testShapePT。
值----------Value----------
a vector of statistics that follows a χ^2 distribution with one degree of freedom under the null hypothesis.
向量的统计χ^2分配如下一零假设下的自由程度。
参考文献----------References----------
A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments. Submitted.
using the Poisson-Tweedie family. Environmetrics 22, pages 152-164.
overdispersed count data by mixtures of poisson variables and poisson processes. Biometrics 53, pages 1225-1238.
参见----------See Also----------
testShapePT
testShapePT
举例----------Examples----------
## Generate a random matrix of counts[#生成随机数矩阵]
counts <- matrix(rPT(n=2000, a=0.5, mu=10, D=5), nrow=20)
## Perform the goodness-of-fit tests for every row in the matrix[#执行矩阵中的每一行,善良的拟合试验]
chi2gof <- gofTest(counts)
## Calculate and sort the corresponding P-values for the[#计算和整理相应的P值]
## null hypothesis that counts follow a negative binomial distribution[#空的假设计算遵循负二项分布]
sort(pchisq(chi2gof, df=1, lower.tail=FALSE))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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