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Data X:
0.88 0.87 0.88 0.89 0.92 0.96 0.99 0.98 0.98 0.98 1.00 1.02 1.06 1.08 1.08 1.08 1.16 1.17 1.14 1.11 1.12 1.17 1.17 1.23 1.26 1.26 1.23 1.20 1.20 1.21 1.23 1.22 1.22 1.25 1.30 1.34 1.31 1.30 1.32 1.29 1.27 1.22 1.20 1.23 1.23 1.20 1.18 1.19 1.21 1.19 1.20 1.23 1.28 1.27 1.27 1.28 1.27 1.26 1.29 1.32
Data Y:
281 295 294 302 314 321 313 310 319 316 319 333 356 358 340 328 355 356 351 359 378 378 389. 407 413 404 406 402 383 392 398 400 405 420 439 441 424 423 434 429 421 430 424 437 456 469 476 510 549 554 557 610 675 596 633 632 596 585 627 629
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R Code
n <- length(x) c <- array(NA,dim=c(401)) l <- array(NA,dim=c(401)) mx <- 0 mxli <- -999 for (i in 1:401) { l[i] <- (i-201)/100 if (l[i] != 0) { x1 <- (x^l[i] - 1) / l[i] } else { x1 <- log(x) } c[i] <- cor(x1,y) if (mx < abs(c[i])) { mx <- abs(c[i]) mxli <- l[i] } } c mx mxli if (mxli != 0) { x1 <- (x^mxli - 1) / mxli } else { x1 <- log(x) } r<-lm(y~x) se <- sqrt(var(r$residuals)) r1 <- lm(y~x1) se1 <- sqrt(var(r1$residuals)) bitmap(file='test1.png') plot(l,c,main='Box-Cox Linearity Plot',xlab='Lambda',ylab='correlation') grid() dev.off() bitmap(file='test2.png') plot(x,y,main='Linear Fit of Original Data',xlab='x',ylab='y') abline(r) grid() mtext(paste('Residual Standard Deviation = ',se)) dev.off() bitmap(file='test3.png') plot(x1,y,main='Linear Fit of Transformed Data',xlab='x',ylab='y') abline(r1) grid() mtext(paste('Residual Standard Deviation = ',se1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Box-Cox Linearity Plot',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations x',header=TRUE) a<-table.element(a,n) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum correlation',header=TRUE) a<-table.element(a,mx) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'optimal lambda(x)',header=TRUE) a<-table.element(a,mxli) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Residual SD (orginial)',header=TRUE) a<-table.element(a,se) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Residual SD (transformed)',header=TRUE) a<-table.element(a,se1) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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