Find the Least Squares Fit - Function : LSFIT

r_lsfit

r_lsfit

Function : LSFIT - Find the Least Squares Fit

Description :

The least squares estimate of b in the model y = X b + e is found.

Usage :

lsfit(x, y, wt = NULL, intercept = TRUE, tolerance = 1e-07, yname = NULL)

Arguments :

x : a matrix whose rows correspond to cases and whose columns correspond to variables.
y : the responses, possibly a matrix if you want to fit multiple left hand sides.
wt : an optional vector of weights for performing weighted least squares.

Example:

x <- c(70, 72, 62, 64, 71, 76, 60, 65, 74, 72)
y <- c(70, 74, 65, 68, 72, 74, 61, 66, 76, 75)
z <- lsfit(x, y)
print(z)
plot(x,y-z$residual,xlim=c(min(x),max(x)),ylim=c(min(y),max(y)),type="l")
par(new=T)
plot(x,y,xlim=c(min(x),max(x)),ylim=c(min(y),max(y)))

r_lsfit

r_lsfit