I am sorry. It was my fault. My example is wrong. I need also rearrange a validation data set too. But I have a sligthy different results with my real data. Where can the problem be?
Andris Jankevics On Otrdiena, 18. Aprīlis 2006 17:55, Andris Jankevics wrote: > Hello useRs, > > I am new user to R and also statistics. Why predicted results in this > example are different? Is the order of variables in X matrix important? > > library (pls) > set.seed (1) > Y1 <- c(1,2,3,4,5,6,7,8,9,10) > Y2 <- c(0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0) > X1 <- rnorm(10,sd=0.2) > X2 <- rnorm(10,sd=1) > X3 <- rnorm(10,sd=0.1) > X4 <- rnorm(10,sd=0.1) > X5 <- rnorm(10,sd=0.1) > > KAL <- data.frame(num=c(1:10)) > KAL$Y <- as.matrix(cbind (Y1,Y2)) > KAL$X <- as.matrix(cbind (X1,X2,X3,X4,X5)) > KAL2 <- data.frame(num=c(1:10)) > KAL2$Y <- as.matrix(cbind (Y1,Y2)) > KAL2$X <- as.matrix(cbind (X5,X4,X3,X2,X1)) > > PLS <- plsr (Y~X,data=KAL, 4,validation = "CV") > PLS2 <- plsr (Y~X,data=KAL2,4, validation = "CV") > > X1v <- rnorm(10,sd=0.1) > X2v <- rnorm(10,sd=1) > X3v <- rnorm(10,sd=0.1) > X4v <- rnorm(10,sd=0.1) > X5v <- rnorm(10,sd=0.1) > VAL <- data.frame(num=c(1:10)) > VAL$X <- as.matrix(cbind(X1v,X2v,X3v,X4v,X5v)) > > predict (PLS,VAL,4) > predict (PLS2,VAL,4) > > Thank You, > > Andris Jankevics > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
