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...Vcorr <- tanh(x[3]) V <- Vsd %o% Vsd V[1,2] <- V[2,1] <- V[1,2] * Vcorr Wsd <- exp(x[4:5]) Wcorr <- tanh(x[6]) W <- Wsd %o% Wsd W[1,2] <- W[2,1] <- W[1,2] * Wcorr return(list( m0 = rep(0,2), C0 = 1e7 * diag(2), FF = diag(2), GG = diag(2), V = V, W = W)) } suMLE <- dlmMLE(NelPlo, rep(0,6), buildSu); suMLE buildSu(suMLE$par)[c("V","W")] Thanking you in advance for your help, Gerardo Amo [[alternative HTML version deleted]]

Hi list, has anyone succeeded in using pgmm() on any dataset besides Arellano/Bond's EmplUK, as shown in the vignette? Whatever I try, I eventually get a runtime error because of a singular matrix at various points in pgmm.diff() (which gets called by pgmm()). For example, when estimating a "dynamic" version of the Grunfeld data: data(Grunfeld, package="Ecdat") grun

Dear R Experts--- Sorry for all the questions yesterday and today. I am trying to use Yves Croissant's pgmm function in the plm package with Blundell-Bond moments. I have read the Blundell-Bond paper, and want to run the simplest model first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning variables yet. the full set of moment conditions recommended for system-GMM,

Dear all, I have looked for an answer for a couple of days, but can't come with any solution. I have a set of functions, say: > t0 <- function(x) {1} > t1 <- function(x) {x} > t2 <- function(x) {x^2} > t3 <- function(x) {x^3} I would like to find a way to add up the previous 4 functions and obtain a new function: > rrr <- function(x) {1+x+x^2+x^3} without,