R plm模型的F检验
我想对plm模型进行f测试,并测试R plm模型的F检验,r,plm,R,Plm,我想对plm模型进行f测试,并测试 model <- plm(y ~ a + b) 及 我试过这样的线性按摩 linearHypothesis(ur.model, c("a", "b")) to test for a = 0 and b = 0 但是我犯了错误 Error in constants(lhs, cnames_symb) : The hypothesis "sgp1" is not well formed: contains bad coefficient/varia
model <- plm(y ~ a + b)
及
我试过这样的线性按摩
linearHypothesis(ur.model, c("a", "b")) to test for a = 0 and b = 0
但是我犯了错误
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
我上面的例子使用的代码稍微简化了一点,如果问题很简单的话。如果问题在细节中,那么这里的实际代码就是
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"))
model3我无法用其中一个内置数据集重现您的错误,即使经过相当多的修改
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"))
可能是因为你在“混合”模型吗?您有一个方差规范,它从以下内容开始:
, ...vcov.=vcovHC(plmmodel1,
。。。但是您使用的是ur.model
如果您提供自己的代码,请确保我们有一个数据集可以试用。下次请提供一个可复制的示例。
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"))
> 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
, ...vcov.=vcovHC(plmmodel1,