search for: richarson

Dear All, I am trying to solve a Generalized Method of Moments problem which necessitate the gradient of moments computation to get the standard errors of estimates. I know optim does not output the gradient, but I can use numericDeriv to get that. My question is: is this the best function to do this? Thank you Jean,

...------------------------------------ for(m in 1:(r - 1)) { for(i in 1:(r - m)) b.mtr[i,]<- (a.mtr[(i+1),]*(4^m)-a.mtr[i,])/(4^m-1) # a.mtr<- b.mtr # a.mtr<- (a.mtr[2:(r+1-m),]*(4^m)-a.mtr[1:(r-m),])/(4^m-1) if(show & m!=(r-1) ) { cat("\n","Richarson improvement group No. ", m, "\n") print(a.mtr[1:(r-m),], 12) } } a.mtr[length(a.mtr)] } ## try it out richardson.grad(function(x){x^3},2) ######################################################################################## Regards, Tolga Uzuner ===========...

...Tcl 8.4.1 is now stable, and I was wondering whether this newer release of Tcl can be used with R under Windows? I've not used Tcl/Tk before but I am considering using it for some applications. Thank you for your time, -Paul Paul Schwarz Department of Forest Science Oregon State University Richarson Hall Corvallis, Oregon 97331 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !...

Hi, Suppose I have an arbitrary function: arbfun<-function(x) {...} Is there a robust implementation of a numerical derivative routine in R which I can use to take it's derivative ? Something a bit more than simple division by delta of the difference of evaluating the function at x and x+delta... Perhaps there is a way to do this using D or deriv but I could not figure it out.

...> for(m in 1:(r - 1)) { > for(i in 1:(r - m)) b.mtr[i,]<- > (a.mtr[(i+1),]*(4^m)-a.mtr[i,])/(4^m-1) > # a.mtr<- b.mtr > # a.mtr<- (a.mtr[2:(r+1-m),]*(4^m)-a.mtr[1:(r-m),])/(4^m-1) > if(show & m!=(r-1) ) { > cat("\n","Richarson improvement group No. ", m, "\n") > print(a.mtr[1:(r-m),], 12) > } > } > a.mtr[length(a.mtr)] > } > > ## try it out > richardson.grad(function(x){x^3},2) > ############################################################## > #############...