search for: twostep

...(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...

...lver that it uses. Ideally, I would wish to figure out a way to be able to choose controls, including the number of iterations, for the solver that I tell gmm() to use. Currently, the way I call the function is as follows: model.name <- gmm(g=g.fn, x=data, gradv=g.gr, t0=c(start), type=c("twostep"), optfct=c("optim") ) I also would want the gmm() function to know that I want it to pass the following control -- maxit=1500 -- to the optim solver. Unfortunately, the 'gmm' manual does not tell whether this is doable. Thanks for your help.

...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 variable...

...t; Do the 5 percentages sum to a constant total? > > If you tell us more about the problem and its context perhaps we can make some suggestions. > > E.g., if you could live with groups of any size that are close > you might try transforming the percentages to z's and applying a TWOSTEP > procedure. > > If your really, really need 5, the use of cluster membership variables > and distances from cluster centers, could be used to limit searches, but > I wouldn't want to try to work it out without more info especially since > I do not presently have SPSS on my s...

...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 Gene...

...) 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)~lo...