I would like to fit a linear model through points (x,y) with standard errors for each of them. So far I used the deming regression, but I couldn't figure out how to force the regression through the origin. Is there a simple method for this problem or do I need to perform a Monte Carlo simulation by variing each measurement point by a random error within the standard deviation and perform statistics with all possible regression lines? Thanks
From R documentation:
"A model with no intercept can be also specified as y ~ x + 0 or y ~ 0 + x"
try
mylm
Thank you Paulo. But this one lm(y~0+x) does not take into account the errors of the y and x values, right?
You could try a weighted linear regression with weights being the ratios of the standard-errors.
Thomas, would
coef( summary( mylm ) ) be suffice?
otherwise, for standard errors
sqrt( diag( vcov( mylm ) ) )
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