[Splm-commits] r20 - pkg

[noreply at r-forge.r-project.org]

Author: gpiras
Date: 2009-10-13 16:01:10 +0200 (Tue, 13 Oct 2009)
New Revision: 20

Removed:
   pkg/REmod.R
Log:
eliminate all functions erroneously  uploaded

Deleted: pkg/REmod.R
===================================================================
--- pkg/REmod.R	2009-10-13 14:00:43 UTC (rev 19)
+++ pkg/REmod.R	2009-10-13 14:01:10 UTC (rev 20)
@@ -1,101 +0,0 @@
-`REmod` <-
-function(X, y, ind, tind, n, k, t, nT, w=NULL, coef0=0,
-         hess=FALSE, trace=trace, x.tol=1.5e-18, rel.tol=1e-15, ...) {
-  ## random effects panel model 'vanilla' ML estimation
-  ## based on general framework, RE structure on errors
-
-  ## MUCH room for optimization! Take framework from ssrRE,
-  ## using kinship etc. (notice inversion of order(ind,tind)!)
-
-  ## Giovanni Millo, Trieste; this version: 22/10/2008.
-
-  ## some useful pieces:
-    Jt<-matrix(1,ncol=t,nrow=t)
-    In<-diag(1,n)
-    It<-diag(1,t)
-    Jbart<-Jt/t
-    Et<-It-Jbart
-
-  ## inverse of Sigma
-    invSigma <- function(phi, n, t) {
-			 invSigma <- 1/(t*phi+1) * kronecker(Jbart, In) + kronecker(Et, In)
-                   invSigma
-                   }
-
-  ## outsource determinant of sigma with an algebraically efficient form!
-
-  ## concentrated likelihood
-    ll.c<-function(phi, y, X, n, t) {
-
-        ## perform GLS
-
-            sigma.1<-invSigma(phi,n,t)
-
-            b.hat<-solve( crossprod(X,sigma.1)%*%X, crossprod(X,sigma.1)%*%y )
-            ehat<-y-X%*%b.hat
-            sigma2ehat<-crossprod(ehat,sigma.1)%*%ehat/(n*t)
-            bhat<-list(betahat=b.hat,e=ehat,sigma2=sigma2ehat)
-
-            e <- bhat[[2]]
-            s2e <- bhat[[3]]
-
-            due <- -n*t/2*log(s2e)
-            tre <- -n/2*log(t*phi+1)
-            quattro <- -1/(2*s2e)*crossprod(e,sigma.1)%*%e
-
-            const <- -(n*t)/2*log(2*pi)
-            ll.c <- const+due+tre+quattro
-            llc <- - ll.c
-            }
-
-  ## iterate (=traballa) until convergence:
-
-  myphi0 <- coef0
-
-  optimum<-nlminb(myphi0, ll.c,
-                  lower=1e-08, upper=1e08,
-                  control=list(x.tol=x.tol, rel.tol=rel.tol, trace=trace),
-                  y=y, X=X, n=n, t=t, ...)
-
-
-  myphi<-optimum$par
-  myll <- optimum$objective
-
-
-  ## optimal values of parms:
-  phi<-myphi
-
-  ## perform GLS
-
-            sigma.1<-invSigma(phi,n,t)
-
-            b.hat<-solve( crossprod(X,sigma.1)%*%X, crossprod(X,sigma.1)%*%y )
-            ehat<-y-X%*%b.hat
-            sigma2ehat<-crossprod(ehat,sigma.1)%*%ehat/(n*t)
-            beta<-list(betahat=b.hat,e=ehat,sigma2=sigma2ehat)
-
-  ## names for coefs and error comp.s
-  nam.beta <- dimnames(X)[[2]]
-  nam.errcomp <- "phi"
-
-  ## calc. cov(b) by GLS
-  covB<-as.numeric(beta[[3]])*solve(crossprod(X,sigma.1)%*%X)
-  dimnames(covB) <- list(nam.beta, nam.beta)
-
-  ## calc. cov(phi) by numerical Hessian
-  covPRL <- -solve(-fdHess(myphi, function(x) -ll.c(x,y,X,n,t))$Hessian)
-  dimnames(covPRL) <- list(nam.errcomp, nam.errcomp)
-
-
-  ## make (separate) coefficients' vectors
-  betas <- as.vector(beta[[1]])
-  errcomp <- phi
-  names(betas) <- nam.beta
-  names(errcomp) <- nam.errcomp
-
-  RES <- list(betas=betas, errcomp=errcomp,
-              covB=covB, covPRL=covPRL, ll=myll)
-
-  return(RES)
-  }
-