当我尝试建模自相关时,为什么会出现错误,即使在Pinheiro和Bates(2009)中完全遵循这个例子？

Question

以下是S和S-Plus第238页混合效果模型的摘录:

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这是我用来重新创建此示例的代码:

library(nlme)
spatDat <- data.frame(x = c(0,0.25,0.5,0.75,1), y = c(0,0.25,0.5,0.50,0.75))
cs1Exp <- corExp(1, form = ~x+y)
cs1Exp <- initialize(cs1Exp, spatDat)

但是当我这样做时,我收到此错误:

Error in getClass(Class) : 
  c("\"corExp\" is not a defined class", "\"corSpatial\" is not a defined class", "\"corStruct\" is not a defined class")
In addition: Warning message:
In if (!is.na(match(Class, .BasicClasses))) return(newBasic(Class,  :
  the condition has length > 1 and only the first element will be used

为什么我会收到此错误？

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附录

R version 2.13.0 (2011-04-13)
Platform: x86_64-pc-linux-gnu (64-bit)
attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] nlme_3.1-101

loaded via a namespace (and not attached):
[1] grid_2.13.0     lattice_0.19-26

Answer 1

其原因是Initialize需要资金I的nlme,因此不能混同initialize的base.然后有Vivi的评论spatdat$y

这有效:

> library(nlme)
> spatDat <- data.frame(x = c(0,0.25,0.5,0.75,1), y = c(0,0.25,0.50,0.75,1.0))
> cs1Exp <- corExp( 1, form = ~x+y )
> cs1Exp <- Initialize( cs1Exp, spatDat )
> corMatrix( cs1Exp )
          [,1]      [,2]      [,3]      [,4]      [,5]
[1,] 1.0000000 0.7021885 0.4930687 0.3462272 0.2431167
[2,] 0.7021885 1.0000000 0.7021885 0.4930687 0.3462272
[3,] 0.4930687 0.7021885 1.0000000 0.7021885 0.4930687
[4,] 0.3462272 0.4930687 0.7021885 1.0000000 0.7021885
[5,] 0.2431167 0.3462272 0.4930687 0.7021885 1.0000000

Answer 2

您的代码存在一些问题.这是更正后的版本:

library(nlme)    
spatDat <- data.frame(x = c(0, 0.25, 0.5, 0.75, 1), y = c(0, 0.25, 0.5, 0.75, 1.0))    
cs1Exp <- corExp(1, form = ~x+y)    
cs1Exp <- Initialize(cs1Exp, spatDat)  
corMatrix(cs1Exp)  

          [,1]      [,2]      [,3]      [,4]      [,5]
[1,] 1.0000000 0.7021885 0.4930687 0.3462272 0.2431167
[2,] 0.7021885 1.0000000 0.7021885 0.4930687 0.3462272
[3,] 0.4930687 0.7021885 1.0000000 0.7021885 0.4930687
[4,] 0.3462272 0.4930687 0.7021885 1.0000000 0.7021885
[5,] 0.2431167 0.3462272 0.4930687 0.7021885 1.0000000