自己先顶一个~~希望早日得到高人指点呀~~这个问题解决不了心理总是觉得很别扭~~纠结呀……

you can try R package "spdep"
Spatial dependence: weighting schemes, statistics and models
###############
library(spdep)
data(oldcol)
test1=moran.test(COL.OLD$CRIME, nb2listw(COL.nb, style="W"))
>test1
        Moran's I test under randomisation

data:  COL.OLD$CRIME  
weights: nb2listw(COL.nb, style = "W")  

Moran I statistic standard deviate = 5.6341, p-value = 8.797e-09
alternative hypothesis: greater
sample estimates:
Moran I statistic       Expectation          Variance
      0.510951264      -0.020833333       0.008908762

######## moran's I - exact test
test2=moran.test(COL.OLD$CRIME, nb2listw(COL.nb, style="W"),
+ randomisation=FALSE)
>test2
        Moran's I test under normality

data:  COL.OLD$CRIME  
weights: nb2listw(COL.nb, style = "W")  

Moran I statistic standard deviate = 5.6754, p-value = 6.92e-09
alternative hypothesis: greater
sample estimates:
Moran I statistic       Expectation          Variance
      0.510951264      -0.020833333       0.008779831

####自行运算如下
statistic standard deviate =(0.5109513-( -0.020833333 ))/sqrt( 0.008779831)=5.6754

alternative == "greater"
p=pnorm(5.6754,lower.tail=FALSE)=6.918248e-09

请问这个是要在stata里面做的吗？？有些复杂啊……

没接触过R,看似复杂其实简单.
约十五分钟一切OK.
http://cran.r-project.org/
Download and Install R
1.Windows
2.base
3.Download R 2.10.1 for Windows (32 megabytes)

安装完后,开启R,
在命令窗口键入install.packages("spdep")
就会自动安装packages("spdep")

package安装完后,就可开始运行,
library(spdep)
data(oldcol)
coords.OLD <- cbind(COL.OLD$X, COL.OLD$Y)
a=moran.test(COL.OLD$CRIME, nb2listw(COL.nb, style="W"),
  randomisation=FALSE)
a

详细function用法,参考spdep.pdf

我也想知道，stata中如何对moran 指数进行显著性检验