[Splm-commits] r17 - pkg

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

Author: gpiras
Date: 2009-10-13 16:00:06 +0200 (Tue, 13 Oct 2009)
New Revision: 17

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

Deleted: pkg/LMHtest.R
===================================================================
--- pkg/LMHtest.R	2009-10-13 13:59:46 UTC (rev 16)
+++ pkg/LMHtest.R	2009-10-13 14:00:06 UTC (rev 17)
@@ -1,97 +0,0 @@
-`LMHtest` <-
-function(formula, data, index=NULL, listw){
-    ## depends on listw2dgCMatrix.R
-  if(!is.null(index)) { ####can be deleted when using the wrapper
-    require(plm)
-    data <- plm.data(data, index)
-    }
-
-  index <- data[,1]
-  tindex <- data[,2]
-
-  x<-model.matrix(formula,data=data)
-  y<-model.response(model.frame(formula,data=data))
-   cl<-match.call()
-	names(index)<-row.names(data)
-  ind<-index[which(names(index)%in%row.names(x))]
-  tind<-tindex[which(names(index)%in%row.names(x))]
-  ## reorder data by cross-sections, then time
-  oo<-order(tind,ind)
-  x<-x[oo,]
-  y<-y[oo]
-  ind<-ind[oo]
-  tind<-tind[oo]
-
-  ## det. number of groups and df
-  N<-length(unique(ind))
-  k<-dim(x)[[2]]
-  ## det. max. group numerosity
-  T<-max(tapply(x[,1],ind,length))
-  ## det. total number of obs. (robust vs. unbalanced panels)
-  NT<-length(ind)
-	ols<-lm(y~x)
-	XpXi<-solve(crossprod(x))
-   n<-dim(ols$model)[1]
-
-	indic<-seq(1,T)
-	inde<-as.numeric(rep(indic,each=N)) ####indicator to get the cross-sectional observations
-	ind1<-seq(1,N)
-	inde1<-as.numeric(rep(ind1,T)) ####indicator to get the time periods observations
-	bOLS<-coefficients(ols)
-	e<-as.matrix(residuals(ols))
-	ee<-crossprod(e)
-####calculate the elements of LMj, LM1, SLM1
-
-		JIe<-tapply(e,inde1,sum)
-		JIe<-rep(JIe,T) ####calculates (J_T kronecker I_N)*u
-		G<-(crossprod(e,JIe)/crossprod(e))-1 ###calculate G in LMj (same notation as in the paper)
-tr<-function(R) sum(diag(R))
-		LM1<-sqrt((NT/(2*(T-1))))*as.numeric(G) ###same notation as in Baltagi et al.
-
-
-####calculate the elements of LMj, LM1, SLM1
-		Wst<-listw2dgCMatrix(listw) ###transform the listw object in a sparse matrix
-		Ws<-t(Wst)  ### this is the real W since listw2dgCMatrix generate W'
-		WWp<-(Ws+Wst)/2 ##generate (W+W')/2
-yy<-function(q){ #### for very big dimension of the data this can be changed looping over the rows and columns of W or either the listw object
-	wq<-WWp%*%q
-	wq<-as.matrix(wq)
-	}
-		IWWpe<-unlist(tapply(e,inde,yy)) ####calculates (I_T kronecker (W+W')/2)*u
-		H<-crossprod(e,IWWpe)/crossprod(e) #calculate H (same notation as in the paper)
-		W2<-Ws%*%Ws ####generate W^2
-		WW<-crossprod(Ws) ####generate W'*W
-		b<-tr(W2+WW) ###generates b (same notation as the paper)
-#		LMj<-(NT/(2*(T-1)))*as.numeric(G)^2 + ((N^2*T)/b)*as.numeric(H)^2   ###LMj as in the paper
-		LM2<-sqrt((N^2*T)/b)*as.numeric(H)^2 ###same notation as in Baltagi et al.
-if (LM1<=0){
-		if (LM2<=0) JOINT<-0
-		else JOINT<-LM2^2
-		}		####this is chi-square_m in teh notation of the paper.
-	else{
-		if (LM2<=0) JOINT<-LM1^2
-		else JOINT<-LM1^2 + LM2^2
-		}
-STAT<- qchisq(0.05,1,lower.tail=FALSE)
-STAT1<- qchisq(0.05,2,lower.tail=FALSE)
-if (JOINT>=2.952) {
-		if (JOINT<7.289 & JOINT>=4.321) pval<-0.05
-		if (JOINT >= 7.289) pval<-0.01
-		if (JOINT<= 4.321)	pval<-0.1
-	}
-else pval<-1
-
-	statistics<-JOINT
-
-  names(statistics)="LM-H"
-	method<- "Baltagi, Song and Koh LM-H one-sided joint test"
-	#alt<-"serial corr. in error terms, sub RE and spatial dependence"
-  ##(insert usual htest features)
-  dname <- deparse(formula)
-  RVAL <- list(statistic = statistics,
-               method = method,
-               p.value = pval, data.name=deparse(formula), alternative="Random Regional Effects and Spatial autocorrelation")
-  class(RVAL) <- "htest"
-  return(RVAL)
-}
-