내용

글번호 257
작성자 heojk
작성일 2016-12-30 12:20:56
제목 lm, rq, rlm 비교
내용 x <- c(32,64,96,118,126,144,152.5,158) y <- c(99.5,104.8,108.5,100,86,64,35.3,15) fit.origin <- lm(y~poly(x,2,raw=TRUE)) y <- c(99.5,104.8,60.5,100,86,64,35.3,15) #3번째 원래 값은 108 xx <- seq(30,160, length=50) plot(x, y, pch=19, ylim=c(0,150)) lines(xx, predict(fit.origin, data.frame(x=xx)), col="red", lty="dashed") fit.lm <- lm(y~poly(x,2,raw=TRUE)) lines(xx, predict(fit.lm, data.frame(x=xx)), col="black") #install.packages("quantreg") library("quantreg") fit.rq <- rq(y ~ poly(x,2,raw=TRUE)) lines(xx, predict(fit.rq, data.frame(x=xx)), col="blue") library("MASS") fit.rlm <- rlm(y ~ poly(x,2,raw=TRUE)) lines(xx, predict(fit.rlm, data.frame(x=xx)), col="purple") legend("topright", inset=0.05, bty="n", legend = c("lm fit to original data", "lm fit", "rq fit", "rlm fit"), lty = c(2, 1, 1, 1), # 1 = "solid" ; 2 = "dashed" col = c("red", "black", "blue", "purple") )