Gmm 函数只能有一个变量矩阵和一个参数向量。你去:
set.seed(123)#to replicate the results
x<-rnorm(50, mean = 3, sd = 2)
y<-rnorm(50, mean = 4, sd = 1)
z_1<-as.matrix(x)
z_2<-as.matrix(y)
z <- cbind(z_1,z_2) #make one matrix from both vectors
e<-function(RGAAA,x) #one input for the parameters and one input for the variables
{m1<-exp(-x[,1]/RGAAA[1])-1
m2<-exp(-x[,2]/RGAAA[2])-1
f<-cbind(m1,m2)
return(f)}
summary(gmm(e,z,c(1,1),method="BFGS",control=1e-12))
使用我的伪随机数种子,您将获得以下输出:
Call:
gmm(g = e, x = z, t0 = c(1, 1), method = "BFGS", control = 1e-12)
Method: twoStep
Kernel: Quadratic Spectral
Coefficients:
Estimate Std. Error t value Pr(>|t|)
Theta[1] 4.5256e+02 3.8809e+01 1.1661e+01 2.0121e-31
Theta[2] 4.9367e+02 1.5265e+01 3.2341e+01 1.8683e-229
J-Test: degrees of freedom is 0
J-test P-value
Test E(g)=0: 0.00577448313404338 *******
#############
Information related to the numerical optimization
Convergence code = 0
Function eval. = 25
Gradian eval. = 24