Function : LM - Fitting Linear Models
Description :
-
lm is used to fit linear models. It can be used to carry out regression, single stratum analysis of variance and analysis of covariance
Usage :
-
lm(formula, data, subset, weights, na.action,
method = "qr", model = TRUE, x = FALSE, y = FALSE, qr = TRUE,
singular.ok = TRUE, contrasts = NULL, offset, ...)
x <- c(70, 72, 62, 64, 71, 76, 60, 65, 74, 72) y <- c(70, 74, 65, 68, 72, 74, 61, 66, 76, 75) data <- data.frame(X=x, Y=y) result <- lm(y~x,data) coefficients(result) names(result) a <- result$coefficients xx <- seq(min(x),max(x),by=0.1) yy <- a[1]+a[2]*xx plot(xx,yy,xlim=c(min(x),max(x)),ylim=c(min(y),max(y)),type="l",xlab="",ylab="") par(new=T) plot(x,y,xlim=c(min(x),max(x)),ylim=c(min(y),max(y)))
See Also ...
- R :: LSFIT ... Find the Least Squares Fit
- R :: NLS ... Nonlinear Least Squares
