Smooth terms are constrained to sum to zero over the covariate values.
This is an identifiability constraint designed to avoid confounding with
the intercept (particularly important if you have more than one smooth).
If you remove the intercept from you model altogether (m2) then the
smooth wil
pe it helps
Anna
Anna Freni Sterrantino
Department of Statistics
University of Bologna, Italy
via Belle Arti 41, 40124 BO.
Da: SAEC
A: r-help@r-project.org
Inviato: Giovedì 11 Ottobre 2012 0:22
Oggetto: [R] GAM without intercept
Hi everybody,
I am trying to
Hi everybody,
I am trying to fit a GAM model without intercept using library mgcv.
However, the result has nothing to do with the observed data. In fact
the predicted points are far from the predicted points obtained from the
model with intercept. For example:
#First I generate some simulated
On Jan 16, 2012, at 9:17 AM, collifu wrote:
Hi all,
I constructed a GAM model with a linear term and two smooth terms,
all of
them statistically significant but the intercept was not
significant. The
adjusted r2 of this model is 0.572 and the deviance 65.3.
I decided to run the model aga
Hi all,
I constructed a GAM model with a linear term and two smooth terms, all of
them statistically significant but the intercept was not significant. The
adjusted r2 of this model is 0.572 and the deviance 65.3.
I decided to run the model again without intercept, so I used in R the
following in
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