Question

我想对plm模型进行f检验并测试

model <- plm(y ~ a + b)

如果

# a = b

和

# a = 0 and b = 0

我尝试过像这样的线性假设

linearHypothesis(ur.model, c("a", "b")) to test for a = 0 and b = 0

但得到了错误

Error in constants(lhs, cnames_symb) : 
  The hypothesis "sgp1" is not well formed: contains bad coefficient/variable names.
Calls: linearHypothesis ... makeHypothesis -> rbind -> Recall -> makeHypothesis -> constants
In addition: Warning message:
In constants(lhs, cnames_symb) : NAs introduced by coercion
Execution halted

上面的例子是代码，如果问题很简单，可以稍微简化一下。如果问题在于细节是这里的实际代码。

model3 <- formula(balance.agr ~ sgp1 + sgp2 + cp + eu + election + gdpchange.imf + ue.ameco)
ur.model<-plm(model3, data=panel.l.fullsample, index=c("country","year"), model="within", effect="twoways")
linearHypothesis(ur.model, c("sgp1", "sgp2"), vcov.=vcovHC(plmmodel1, method="arellano", type = "HC1", clustering="group"))

Answer 1

我无法使用其中一个内置数据集重现您的错误，即使经过相当多的摆弄也是如此。

这对你有用吗？

require(plm)
require(car)
data(Grunfeld)
form <- formula(inv ~ value + capital)
re <- plm(form, data = Grunfeld, model = "within", effect = "twoways")
linearHypothesis(re, c("value", "capital"), 
                 vcov. = vcovHC(re, method="arellano", type = "HC1"))

另请注意，您在显示的更复杂的代码中似乎有错误。您在对象linearHypothesis()上使用ur.model，但在对象vcovHC()上调用plmmodel1。不确定这是不是问题，但请检查以防万一。

是否可以提供数据？最后，编辑您的问题以包含sessionInfo()的输出。我的（来自相当繁忙的R实例）：

> sessionInfo()
R version 2.11.1 Patched (2010-08-25 r52803)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_GB.utf8       LC_NUMERIC=C             
 [3] LC_TIME=en_GB.utf8        LC_COLLATE=en_GB.utf8    
 [5] LC_MONETARY=C             LC_MESSAGES=en_GB.utf8   
 [7] LC_PAPER=en_GB.utf8       LC_NAME=C                
 [9] LC_ADDRESS=C              LC_TELEPHONE=C           
[11] LC_MEASUREMENT=en_GB.utf8 LC_IDENTIFICATION=C      

attached base packages:
[1] splines   grid      stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] car_2.0-2        nnet_7.3-1       plm_1.2-6        Formula_1.0-0   
 [5] kinship_1.1.0-23 lattice_0.19-11  nlme_3.1-96      survival_2.35-8 
 [9] mgcv_1.6-2       chron_2.3-37     MASS_7.3-7       vegan_1.17-4    
[13] lmtest_0.9-27    sandwich_2.2-6   zoo_1.6-4        moments_0.11    
[17] ggplot2_0.8.8    proto_0.3-8      reshape_0.8.3    plyr_1.2.1      

loaded via a namespace (and not attached):
[1] Matrix_0.999375-44 tools_2.11.1

Answer 2

可能是因为你正在“混合”模特吗？您有一个开始的方差规范：

, ...vcov.=vcovHC(plmmodel1,

...但您正在使用ur.model。

用plm模型进行F检验

2 个答案: