Greetings to every body.

we know that for linear regression: two-parameter fitting in R: (for a and
b as slope and intercept)

[a] for y=ax+b type models we use: lm(y~x)
[b] for y=ax    type models we use:  lm(y~0+x)  => forced to pass through
origin

Now I have question:   what about y=b  fitting?  is there any model to
force or  impose the ax to be zero

Let say

x <- c(1,2,3,4,5,6,7,8,9)
y <- c( 0.853,0.852, 0.854, 0.858, 0.862, 0.856, 0.858, 0.857, 0.863)
plot(y~x, xlim=c(0,10), ylim=c(0,1))
abline(lm(y~x),col="blue")  # this doesn't give exact horizontal  but
slightly inclined.

or is it as simple as, just find the intercept using the lm(y~x) , then
abline(h=intercept,col="red") ?

any comment or advice is greatly appreciated ;)

	[[alternative HTML version deleted]]

