(i know it must be incredibely easy, but i'm strugling with it in R:)
i have dataset of x and y values saved in X and Y vectors. I know that plot of the data should follow exactly -45 degree line (see image below)
How do i find such -45 degree line that best fits the data (+ all these statistics available from summary(lm(...))? I've tried lm, but i can't force it to abandon fitting the slope parameter
Thank you
After trying: lm(y~1,offset=-x)
and applying abline(coefficient, -1)
i obtain following plot (see below)
black line is abline plot, yellow one is mine guess of fit -- what's wrong with lm
or do i miss totally something?
I believe the solution from @BenBolker is correct and perhaps you are using the wrong coefficient:
lm1 <- lm(y~1,offset=-x,data=df)
plot(df)
abline(coefficients(lm1),-1)
This produces:
This fit looks like the correct fit to me. The intercept is -2.217.