analyse.models(scrime)
analyse.models()所属R语言包：scrime
Summarize MCMC sample of Bayesian logic regression models
总结MCMC贝叶斯逻辑回归模型的样本
译者：生物统计家园网 机器人LoveR
描述----------Description----------
For an MCMC sample of Bayesian logic regression models obtained with fblr the distribution of the model size and the most common logic predictors with up to three binaries are reported.
对于MCMC抽样的贝叶斯逻辑回归模型得到的fblr分布模型的大小，最常见的逻辑的预测与三个二进制文件的报告。
用法----------Usage----------
analyse.models(file, size.freq = TRUE, moco = c(20, 10), int.freq = TRUE,
kmax = 10, int.level = 2, bin.names = NULL)
参数----------Arguments----------
参数：file
character string naming file where MCMC output of fblr is stored.
MCMC输出fblr存储的字符串命名文件。
参数：size.freq
determines whether distribution of model size is reported as frequencies (default) or proportions.
模型的大小决定分配报告的频率（默认）或比例。
参数：moco
a vector of length 2 or 3 that determines how many of the most common main effects, two-factor interactions and (possibly) three-factor interactions are reported.
的矢量的长度为2或3，用于确定如何最常见的主效应，两个因素之间的相互作用和（可能的）三因子相互作用的许多报告。
参数：int.freq
determines whether the number (default) or the proportion of models containing a specific interaction is reported.
确定的数目（默认）或模型的比例含有特定的相互作用是否报告。
参数：kmax
the maximum number of allowed logic predictors used in fblr.
用于fblr允许逻辑预测因子的最大数目。
参数：int.level
the maximum number of allowed binaries in a logic predictor used in fblr.
的最大允许二进制文件中使用一个逻辑的预测中fblr。
参数：bin.names
character vector of names for the binary variables. If no names are supplied, binaries are referred to with their indices.
字符向量为二进制变量的名称。如果没有提供名字，二进制文件被称为他们的指数。
Details
详细信息----------Details----------
The logic regression models visited during the MCMC run are stored by fblr in the rows of a matrix in the following fashion: Position 1 contains the number of logic predictors in the model. The next kmax * (int.level + 1) positions contain the predictors, each predictor being coded as c(number of binaries in predictor, indices of binaries), where negative indices denote the complement of a variable. It follow the log-likelihood of the model, the value of the precision of the regression parameters and the kmax+1 regression parameters. Zeros indicate empty entries. analyse.models extracts some of the most interesting information, namely which logic predictors occur most often in the visited models, from the sample. The complement of a binary is indicated with a minus sign preceding its name.
参观了的MCMC运行过程中的逻辑回归模型存储fblr在以下方式中的矩阵：第1行，在模型中包含的数字逻辑的预测。下一个kmax * (int.level + 1)位置包含的预测，每个预测被编码为C（预测数的二进制文件中，指数的二进制文件），其中负指数表示的补变量。它遵循的模式，价值回归参数的精度和kmax+1回归参数的对数似然。零表示空项。 analyse.models提取一些最有趣的信息，即逻辑的预测发生的最经常访问的模式，从样品。与它的名字前的减号表示一个二进制的补。
值----------Value----------
<table summary="R valueblock"> <tr valign="top"><td>size</td> <td> table of model sizes.</td></tr> <tr valign="top"><td>ones</td> <td> table of the moco[1] most common single-binary predictors.</td></tr> <tr valign="top"><td>twos</td> <td> table of the moco[2] most common two-binaries predictors.</td></tr> <tr valign="top"><td>threes</td> <td> table of the moco[3] most common three-binaries predictors.</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD> size</ TD>的模型尺寸<TD>表。</ TD> </ TR> <TR VALIGN =“顶“<TD> ones</ TD> <TD>表的moco[1]的最常见的单一二进制的预测。</ TD> </ TR> <tr valign="top"> < twos TD> </ TD> <TD>表的moco[2]的最常见的两个二进制文件的预测。</ TD> </ TR> <tr valign="top"> <TD> X> </ TD> <TD>表的threes的最常见的三个二进制文件的预测。</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Arno Fritsch, <a href="mailto:arno.fritsch@uni-dortmund.de">arno.fritsch@uni-dortmund.de</a>
参见----------See Also----------
fblr, predictFBLR
fblr，predictFBLR
实例----------Examples----------
# Use fblr on some simulated SNP data[使用fblr一些模拟的SNP数据]
snp <- matrix(rbinom(500*20,2,0.3),ncol=20)
bin <- snp2bin(snp)
int <- apply(bin,1,function(x) (x[1] == 1 & x[3] == 0)*1)
case.prob <- exp(-0.5+log(5)*int)/(1+exp(-0.5+log(5)*int))
y <- rbinom(nrow(snp),1,prob=case.prob)
fblr(y, bin, niter=1000, nburn=0)
analyse.models("fblr_mcmc.txt")
# with SNP names[与SNP名称]
name.snp <- LETTERS[1:20]
name.bin <- paste(rep(name.snp,each=2), c("_d","_r"),sep="")
analyse.models("fblr_mcmc.txt", bin.names=name.bin)
## End(Not run)[＃（不执行）]
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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 2012-9-29 23:01:37
