You can some time manually substitute a categorical variable with a set
of continuous variables.
For example, you have the variables like "landcover.class" with 3 values
"class A, class B, class C". You cna transform it into 3 continuous
variables landcover.class.A, landcover.class.B, landcover.class.C and
assign a value of 1 or 100% for elements belonging to that class or of 0
for elements not belonging.
That help some time.
Regards
Noah Silverman wrote:
Steve,
I get that. What you wrote make sense.
My challenge is the data I'm attempting to model. Some of the
variables are continuous, some are factors. both linear and poisson
models work. (Poisson doing a much more accurate job.) However, some
of the numerical variables are clearly non-linear. Hence my interest
in GAM. I suppose one alternative would be to try some polynomial
transformation on the variable as part of a Poisson model.
Any other suggestions would be welcome.
Thanks!
-N
On 3/19/10 8:37 PM, Steven McKinney wrote:
Hi Noah
GAM models were developed to assess the functional form
of the relationship of continuous predictor variables to the
response, so weren't really meant to handle factor variables
as predictor variables. GAMs are of the form
E(Y | X1, X2, ...) = So + S(X1) + S(X2) + ...
where S(X) is a smooth function of X.
Hence you might want to rethink why you'd want a
factor variable as a predictor variable in a GAM.
This is why the gam machinery doesn't just do the
factor conversion to indicator variables as is done in
lm.
HTH
Steven McKinney
________________________________________
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On
Behalf Of Noah Silverman [n...@smartmediacorp.com]
Sent: March 19, 2010 12:54 PM
To: r-help@r-project.org
Subject: [R] Factor variables with GAM models
I'm just starting to learn about GAM models.
When using the lm function in R, any factors I have in my data set are
automatically converted into a series of binomial variables.
For example, if I have a data.frame with a column named color and values
"red", "green", "blue". The lm function automatically replaces it with
3 variables colorred, colorgreen, colorblue which are binomial {0,1}
When I use the gam function, R doesn't do this so I get an error.
1) Is there a way to ask the gam function to do this conversion for me?
2) If not, is there some other tool or utility to make this data
transformation easy?
3) Last option - can I use lm to transform the data and then extract it
into a new data.frame to then pass to gam?
Thanks!!!
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______________________________________________
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--
Corrado Topi
PhD Researcher
Global Climate Change and Biodiversity
Area 18,Department of Biology
University of York, York, YO10 5YW, UK
Phone: + 44 (0) 1904 328645, E-mail: ct...@york.ac.uk
______________________________________________
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and provide commented, minimal, self-contained, reproducible code.
