How to interprete the results of panel data models of R? I estimate a adapted form of Koenker's (2004) suggestion for a quantile regression approach with panel data, for my data:
rq.fit.panel <- function(X,Y,s,w,taus,lambda) { require(SparseM) require(quantreg) K <- length(w) if(K != length(taus)) stop("length of w and taus must match") X <- as.matrix(X) p <- ncol(X) n <- length(levels(as.factor(s))) N <- length(y) if(N != length(s) || N != nrow(X)) stop("dimensions of y,X,s must match") Z <- as.matrix.csr(model.matrix(~as.factor(s)-1)) Fidelity <- cbind(as(w,"matrix.diag.csr") %x% X,w %x% Z) Penalty <- cbind(as.matrix.csr(0,n,K*p),lambda*as(n,"matrix.diag.csr")) D <- rbind(Fidelity,Penalty) y <- c(w %x% y,rep(0,n)) a <- c((w*(1-taus)) %x% (t(X)%*%rep(1,N)), sum(w*(1-taus)) * (t(Z) %*% rep(1,N)) + lambda * rep(1,n)) rq.fit.sfn(D,y,rhs=a) How to interprete the results of panel data models of R? I estimate a adapted form of Koenker's (2004) suggestion for a quantile regression approach with panel data, for my data: rq.fit.panel <- function(X,Y,s,w,taus,lambda) { require(SparseM) require(quantreg) K <- length(w) if(K != length(taus)) stop("length of w and taus must match") X <- as.matrix(X) p <- ncol(X) n <- length(levels(as.factor(s))) N <- length(y) if(N != length(s) || N != nrow(X)) stop("dimensions of y,X,s must match") Z <- as.matrix.csr(model.matrix(~as.factor(s)-1)) Fidelity <- cbind(as(w,"matrix.diag.csr") %x% X,w %x% Z) Penalty <- cbind(as.matrix.csr(0,n,K*p),lambda*as(n,"matrix.diag.csr")) D <- rbind(Fidelity,Penalty) y <- c(w %x% y,rep(0,n)) a <- c((w*(1-taus)) %x% (t(X)%*%rep(1,N)), sum(w*(1-taus)) * (t(Z) %*% rep(1,N)) + lambda * rep(1,n)) rq.fit.sfn(D,y,rhs=a) } bdeduc2<-read.table("dados_rq.txt", header=T) z<-c("inter","ne","no","su","co") X<-bdeduc2[,z] y<-bdeduc2$scoreedu s<-bdeduc2$uf w<-c(0.1,0.25,0.5,0.25,0.1) taus<-c(0.1,0.25,0.5,0.75,0.9) lambda<-1 How to interprete the results of panel data models of R? I estimate a adapted form of Koenker's (2004) suggestion for a quantile regression approach with panel data, for my data: rq.fit.panel <- function(X,Y,s,w,taus,lambda) { require(SparseM) require(quantreg) K <- length(w) if(K != length(taus)) stop("length of w and taus must match") X <- as.matrix(X) p <- ncol(X) n <- length(levels(as.factor(s))) N <- length(y) if(N != length(s) || N != nrow(X)) stop("dimensions of y,X,s must match") Z <- as.matrix.csr(model.matrix(~as.factor(s)-1)) Fidelity <- cbind(as(w,"matrix.diag.csr") %x% X,w %x% Z) Penalty <- cbind(as.matrix.csr(0,n,K*p),lambda*as(n,"matrix.diag.csr")) D <- rbind(Fidelity,Penalty) y <- c(w %x% y,rep(0,n)) a <- c((w*(1-taus)) %x% (t(X)%*%rep(1,N)), sum(w*(1-taus)) * (t(Z) %*% rep(1,N)) + lambda * rep(1,n)) rq.fit.sfn(D,y,rhs=a) }enter code here bdeduc2<-read.table("dados_rq.txt", header=T) z<-c("inter","ne","no","su","co") X<-bdeduc2[,z] y<-bdeduc2$scoreedu s<-bdeduc2$uf w<-c(0.1,0.25,0.5,0.25,0.1) taus<-c(0.1,0.25,0.5,0.75,0.9) lambda<-1 But i don't have the estimate significances, i don't know identify the results below: $coef [1] 1.02281339 -0.18750668 -0.13688807 -0.04180458 -0.01367417 1.02872440 -0.18055062 -0.13003224 -0.03829135 -0.01409369 1.03377335 -0.16649845 -0.11669812 [14] -0.03854060 -0.01438620 1.03851101 -0.15328087 -0.10440359 -0.03871744 -0.01465492 1.04330584 -0.14660960 -0.09670756 -0.03465501 -0.01430647 -0.29187982 Anybody help me? [27] -0.21831160 -0.11295134 -0.21530494 -0.15664777 -0.13840296 -0.03224749 -0.11692122 -0.11237144 -0.15112171 -0.10385352 -0.08385934 -0.16090525 -0.30349309 [40] -0.16121494 -0.03106264 -0.16299994 -0.03182579 -0.22271685 -0.08251486 -0.29031224 -0.19680023 -0.20004209 -0.05601186 -0.21140762 -0.04254752 -0.01864703 $ierr [1] 0 $it [1] 16 $time [1] 0 ##summary rq summary(rq) Length Class Mode coef 52 -none- numeric ierr 1 -none- numeric it 1 -none- numeric time 1 -none- numeric -- View this message in context: http://r.789695.n4.nabble.com/Question-of-Quantile-Regression-for-Longitudinal-Data-tp883458p3303668.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.