【发布时间】：2014-11-10 09:28:19
【问题描述】：
我正在尝试对来自 R 中的 BayesVarSel 包的数据集 Ozone35 运行 Gibbs 采样方案。
这是数据集 Ozone35 的信息：
A data frame with 178 observations on the following 36 variables.
y Response = Daily maximum 1-hour-average ozone reading (ppm) at Upland, CA
x4 500-millibar pressure height (m) measured at Vandenberg AFB
x5 Wind speed (mph) at Los Angeles International Airport (LAX)
x6 Humidity (percentage) at LAX
x7 Temperature (Fahrenheit degrees) measured at Sandburg, CA
x8 Inversion base height (feet) at LAX
x9 Pressure gradient (mm Hg) from LAX to Daggett, CA
x10 Visibility (miles) measured at LAX
x4.x4 =x4*x4
x4.x5 =x4*x5
x4.x6 =x4*x6
x4.x7 =x4*x7
x4.x8 =x4*x8
x4.x9 =x4*x9
x4.x10 =x4*x1010 Ozone35
x5.x5 =x5*x5
x5.x6 =x5*x6
x5.x7 =x5*x7
x5.x8 =x5*x8
x5.x9 =x5*x9
x5.x10 =x5*x10
x6.x6 =x6*x6
x6.x7 =x6*x7
x6.x8 =x6*x8
x6.x9 =x6*x9
x6.x10 =x6*x10
x7.x7 =x7*x7
x7.x8 =x7*x8
x7.x9 =x7*x9
x7.x10 =x7*x10
x8.x8 =x8*x8
x8.x9 =x8*x9
x8.x10 =x8*x10
x9.x9 =x9*x9
x9.x10 =x9*x10
x10.x10 =x10*x10
我运行了以下 Gibbs 抽样方案来确定最佳模型：
Oz35.GibbsBvs<- GibbsBvs(formula="y~.", data=Ozone35, prior.betas="gZellner",
prior.models="Constant", n.iter=10000,
init.model="null",n.burnin=100, time.test = FALSE)
但是，当我运行以下代码时，我收到错误消息“plot.new() 中的错误：图形边距太大”：
plotBvs(Oz35.GibbsBvs, option="conditional")
任何帮助将不胜感激。
【问题讨论】：
标签： r regression bayesian