Solving for 2 variables under GMM -


i tried solve 2*1 matrix of gmm estimators following code:

x<-rnorm(50, mean = 3, sd = 2) y<-rnorm(50, mean = 4, sd = 1) z_1<-as.matrix(x) z_2<-as.matrix(y) e<-function(rgaaa,x,y)           {m1<-exp(-x/rgaaa[1])-1           m2<-exp(-y/rgaaa[2])-1           f<-cbind(m1,m2)             return(f)}   summary(gmm(e,cbind(z_1,z_2),c(1,1),method="bfgs",control=1e-12))

however, yield error message:

error in p$g(p$t0, x) : argument "y" missing, no default

could me find out went wrong? lot!

the gmm function can have 1 matrix variables , 1 vector parameters. there go:

set.seed(123)#to replicate 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 1 matrix both vectors e<-function(rgaaa,x) #one input parameters , 1 input 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))

and seed pseudo-random numbers following output:

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 0                  j-test               p-value             test e(g)=0:    0.00577448313404338  *******              ############# information related numerical optimization convergence code =  0  function eval. =  25  gradian eval. =  24

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