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
