Plot appropriate priors using parameters from vector
图适当使用向量参数先验
用法----------Usage----------
plotPriors(parameter.vec)
参数----------Arguments----------
参数:parameter.vec
MCMC parameter vector of the type generated by e.g. mcmc.defaultParams_Linear
如产生类型的MCMC参数向量mcmc.defaultParams_Linear
Details
详情----------Details----------
This function takes the parameter vector that will be used for network inference function and plots the priors associated with the parameters given.
此功能需要将网络推理功能和图与给定的参数相关联的先验参数向量。
参考文献----------References----------
networks using time course data with repeated measurements. Bioinformatics 2010; doi: 10.1093/bioinformatics/btq421
topology of a nonlinear sparse gene regulatory network using fully Bayesian spline autoregression Biostatistics 2011; doi: 10.1093/biostatistics/kxr009
# Get default parameters[获取默认参数]
nonLinearNet.params <- mcmc.defaultParams_nonLinear()
# Change run length[变更运行长度]
nonLinearNet.params[1] <- 150000
# Change prior on smoothness parameter[改变之前对平滑参数]
nonLinearNet.params[6] <- 30000 # Change truncation [改变截断]
nonLinearNet.params[12] <- 3 # Concentrate more mass close to linear region[集中更多的质量接近线性区]
# Plot to check changes[图检查更改]
plotPriors(nonLinearNet.params)