You should consult a linear models text, but, assuming I have
correctly understood your post, the procedure is this (the translation
to R code is trivial, and I leave it to you):
Let y be the response variable, P1 be the first set of predictors and
z be your new predictor to be added.
1. regress
.com
>-Original Message-
>From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Urs
>Kleinholdermann
>Sent: Wednesday, May 17, 2017 09:12
>To: r-help@r-project.org
>Subject: [R] adding predictor to linear model without changing existing
>coefficients
>
>D
Dear list members,
I want to add a predictor to a linear model without changing the
coefficients of the existing model. How is that done with R?
So if I have a response y and predictors x1, x2, x3 I want to make a model lm1
like
lm1 = lm(y~x1+x2)
After this model is computed I want to add x3 l
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