search for: onestep

...allocate memory) Is this contributing to my problem? Even if it isn't what can I do to stop this filling up the log. What could possibly be causing slow writes back to the shared drive Apart from the above error message - the server doesn't appear to showing any other errors Tony Baker OneStep Solutions LLP Suite 8&9 Hadleigh Business Centre 351 London Road Hadleigh Essex SS7 2BT T-01702 426400 F-01702 556855 tony at onestep.co.uk This email, including any attachments, is confidential and intended solely for the person or organisation to whom it is addressed. If you are not the int...

Hi I have the following formula (I hope it is clear - if no, I can try to do better the next time) h(x, a, b) = integral(0 to pi/2) ( ( integral(D/sin(alpha) to Inf) ( ( f(x, a, b) ) dx ) dalpha ) and I want to do an mle with it. I know how to use mle() and I also know about integrate(). My problem is to give the parameter values a and b to the

I have a PDC which is a Sun280R with Solaris 8 running PCNetlink2.0 (effectively a WindowsNT4.0 server) I want to join a Apple G5 with MacOSX10.3.3 (Samba 3.0) as a domain member of the above PDC. It will not allow me to do this and has lots of "master browser - unknown" in the logs of the Apple. I have the IP address in the same range as the PDC and have the netmask set the same

...on mine...). The system-GMM estimator (with robust SEs) in Stata is 'xtabond2 n nL1, gmm(L.(n)) nomata robust' whose R equivalent is: > sysmod<-pgmm( dynformula( log(emp) ~ 1, list(1)), data=EmplUK, gmm.inst=~log(emp), lag.gmm=c(2,99), + effect="individual", model="onestep", transformation="ld" ) > summary(sysmod, robust=TRUE) (note that although 'summary(sysmod)' does not report a constant, it's actually there; this is an issue to be checked). while the difference-GMM is 'xtabond2 n nL1, gmm(L.(n)) noleveleq nomata robust', in...

...nts in this model. There just should be the "gmm-instruments" I need for the model. In order to estimate it, I tried the following code: > > library(plm) > > test <- pgmm(Y ~ lag(Y, 1) + X1 + X2 + X3 | lag(Y, 1), data=Model, > effect="individual", model="onestep") > > I tried "Model" as "Modelp <- pdata.frame(..." and as "Model <- read.table(..." but in both cases there?s an error-massage: Error in solve.default(Reduce("+", A2)) : System ist f?r den Rechner singul?r: reziproke Konditionszahl =...

Hi, I want to estimate a dynamic paneldata model with the following code, but unfortenately I received the error message below. form<-PB~Activity+Solvency+Cap_Int dynpanel<-pgmm(dynformula(form,list(1,1,1,1)),data=panel[1:2185,1:37],effect="twoways",model="onestep",index=c("Aktie","Datum"),gmm.inst=~PB,lag.gmm=list(c(2,12)),transformation="ld") Fehler in FUN(X[[1L]], ...) : Indizierung au?erhalb der Grenzen dim(panel) [1] 34086 37 Best regards, Marco -- GRATIS f?r alle GMX-Mitglieder: Die maxdome Movie-FLAT!

...ct "arglist1" not found The full stack looks like this: > profile(m0f,skiperrs=FALSE) Error in is.vector(X) : object "arglist1" not found Enter a frame number, or 0 to exit 1: profile(m0f, skiperrs = FALSE) 2: profile(m0f, skiperrs = FALSE) 3: .local(fitted, ...) 4: onestep(step) 5: eval.parent(call, 2) 6: eval(expr, p) 7: eval(expr, envir, enclos) 8: mle2(minuslogl = function (lmu = NULL, ltheta = NULL) 9: optim(start, objectivefunction, method = method, hessian = TRUE, ...) 10: function (par) 11: fn(par, ...) 12: do.call("minuslogl", args, envir = env...

...optimization is the previous best-fit solution, rather than the overall MLEs of the parameters. Actually fairly easy to implement (I think: I haven't really tested that it works on anything hard, just that it doesn't seem to break profiling) -- requires pfit to be assigned globally within onestep() and a few lines of code further down. added an AIC method for mle objects collapsed the absVal/!absVal code cases slightly added a "sqrVal" argument for those who want to see the value of the log-likelihood, not the square root or signed square root (could be collapsed into a "s...

.... On the other hand, the exact NF number at which pgmm() dies does suggest that you are right. function( NF=7, NT=4 ) { d= data.frame( firm= rep(1:NF, each=NT), year= rep( 1:NT, NF), x=rnorm(NF*NT) ) lagformula= dynformula( x ~ 1, list(1) ) v=pgmm( lagformula, data=d, gmm.inst=~x, model="onestep", effect=NULL, lag.gmm=c(1,99), transformation="ld" ) } with NF=8, it works; and with NF=7, it dies. With NF=7, I have 28 data points in levels and 21 data points in differences, which are used to estimate only one auto-coefficient via 4 moment conditions. (Is this correct?)...

...uced in: dweibull(x, shape, scale, log) 4: NaNs produced in: dweibull(x, shape, scale, log) What can I do to avoid this problem? The second one is following the second call of mle: summary(fit.NE) gives me the summary of the fit, but profile(fit.NE) gives me the following error message: Error in onestep(step) : profiling has found a better solution, so original fit had not converged In addition: Warning messages: 1: NaNs produced in: dexp(x, 1/rate, log) 2: NaNs produced in: dexp(x, 1/rate, log) 3: NaNs produced in: dexp(x, 1/rate, log) 4: NaNs produced in: dexp(x, 1/rate, log) 5: NaNs produced in...

...on mine...). The system-GMM estimator (with robust SEs) in Stata is 'xtabond2 n nL1, gmm(L.(n)) nomata robust' whose R equivalent is: > sysmod<-pgmm( dynformula( log(emp) ~ 1, list(1)), data=EmplUK, gmm.inst=~log(emp), lag.gmm=c(2,99),  + effect="individual", model="onestep", transformation="ld" ) > summary(sysmod, robust=TRUE) (note that although 'summary(sysmod)' does not report a constant, it's actually there; this is an issue to be checked). while the difference-GMM is 'xtabond2 n nL1, gmm(L.(n)) noleveleq nomata robust', in...