search for: twosteps

...(which gets called by pgmm()). For example, when estimating a "dynamic" version of the Grunfeld data: data(Grunfeld, package="Ecdat") grun <- pgmm(dynformula(inv ~ value + capital, lag=list(1,1,1), log=T), data=Grunfeld, gmm.inst=~log(inv), lag.gmm=list(c(2,5)), model="twosteps") Error in solve.default(suml(A2)) : system is computationally singular: reciprocal condition number = 8.83721e-21 I read all the documentation available and tried stepping through the source code, but pgmm.diff() is not exactly the easiest function to understand, especially given R's...

Hello -- The question I have is about the gmm() function from the 'gmm' package (v. 1.4-5). The manual accompanying the package says that the gmm() function is programmed to use either of four numerical solvers -- optim, optimize, constrOptim, or nlminb -- for the minimization of the GMM objective function. I wonder whether there is a way to pass controls to a solver used while calling

...data1.gmm <- pgmm(dynformula(lnsales_rank ~ ln_price + avg_ham_rate + avg_spam_rate + num_of_ham+ num_of_spam + ship_code2 +ship_code3 +ship_code4+ ship_code5+ ship_code6 + ship_ code7, lag = list(0, 0, 0, 0,0,0,0,0,0,0,0,0), log =FALSE), data=data, effect = "individual", model = "twosteps", transformation = "ld",gmm.inst = ~ ln_price, lag.gmm =2) However, error message: Error in solve.default(Reduce("+", A1)) : system is computationally singular: reciprocal condition number = 6.36689e-23" shown. I found that skipping one of the ship_code variables...

Art (and group), I'm doing this as a form of missing value analysis. Approximately 30% of the cases are missing data for one variable. To impute values for those cases, I'd like to match those cases that are missing the variable to all other cases and then take an average of those to infill. I realize there are many methods for imputing data. I'm not well versed on any in

...xtabond2 n L(0/1).(l.n w) l(0/2).(k ys) yr198?c cons, gmm(L.n) iv(L(0/1).w l(0/2).(k ys) yr198?c cons) noleveleq noconstant two nomata replicated by: > mymod2<-pgmm(dynformula(log(emp)~log(wage)+log(capital)+log(output),list(2,1,2,2)), + data=EmplUK, effect="twoways", model="twosteps", + gmm.inst=~log(emp), lag.gmm=list(c(2,99)), transformation="d") > summary(mymod2) * Column (b) xtabond2 n L(0/1).(l.n ys w) k yr198?c cons, gmm(L.n) iv(L(0/1).(ys w) k yr198?c cons) noleveleq noconstant two nomata replicated by: > abmod3<-pgmm(dynformula(log(emp)~...

...nts) <- c(namesX, namest) : 'names' attribute [13] must be the same length as the vector [5]". My command is: reg.gmm<-pgmm(dynformula(ln_per_co2ec~ln_per_realgdp+ln_per_realgdp2,lag .form=list(1,0,0), log.form=FALSE),data=co2new,effect="individual",model="twosteps", gmm.inst=~ln_per_co2ec,lag.gmm=list(c(99,2)),transformation="d") Could you guys give me some hints on this problem? Thank you in advance. Best regards Limin -------------------------------------------------------- Giovanni Millo Research Dept., Assicurazioni Gener...

...) xtabond2 n L(0/1).(l.n w) l(0/2).(k ys) yr198?c cons, gmm(L.n) iv(L(0/1).w l(0/2).(k ys) yr198?c cons) noleveleq noconstant two nomata replicated by: > mymod2<-pgmm(dynformula(log(emp)~log(wage)+log(capital)+log(output),list(2,1,2,2)), + data=EmplUK, effect="twoways", model="twosteps", + gmm.inst=~log(emp), lag.gmm=list(c(2,99)), transformation="d") > summary(mymod2) * Column (b) xtabond2 n L(0/1).(l.n ys w) k yr198?c cons, gmm(L.n) iv(L(0/1).(ys w) k yr198?c cons) noleveleq noconstant two nomata replicated by: > abmod3<-pgmm(dynformula(log(emp)~log...