Usage: |
gamfit(t,y{,opt})
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Input: |
| t | n x p matrix, the predictor variables.
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| y | n x 1 vector , the observed
response variables
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| opt | optional, a list with optional input. The macro
"gamopt" can be used to set up this parameter.
The order of the list elements is not important.
Parameters which are not given are replaced by
deflts (see below).
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| opt.x | n x d matrix, the discrete predictor variables.
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| opt.h | p x 1 or 1 x 1 matrix , chosen bandwidth for
the directions of interest
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| opt.g | p x 1 or 1 x 1 matrix , chosen bandwidth for
the directions not of interest
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| opt.loc | dummy , for loc=0 local constant (Nad. Wats.),
for loc=1 local linear and for loc=2 local
quadratic estimator will be used
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| opt.kern | string, specifying the kernel function for backfitting
algorithm
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| opt.tg | ng x pg vector, a grid for continuous part. If tg is
given, the nonparametric function will be
computed on this grid.
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| opt.shf | integer, (show-how-far) if exists and =1, an output
is produced which indicates how the iteration
is going on (additive function / point of estimation /
number of iteration).
|
| opt.code | text string, the short code for the model (e.g.
"bilo" for logit or "noid" for ordinary PLM).
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| opt.wx | scalar or n x 1 vector, prior weights. If not given,
all weights are set to 1.
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| opt.off | scalar or n x 1 vector, offset in linear predictor.
If not given, set to 0.
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| opt.name | string, prefix for the output. If not given, "gam"
is used.
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| opt.xvars | p x 1 string vector, variable names for the output.
Note, that only up to 11 characters are used.
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Output: |
| gampic or opt.name+"pic" | display, containing estimation result
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| gamfit | list object, which is made
globally available
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| gamfit.m | estimator for the non-linear part
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| gamfit.b | p x 1 vector, estimated coefficients of the linear part
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| gamfit.bv | p x p matrix, estimated covariance matrix for b.
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| gamfit.const | scalar, estimated constant.
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| gamfit.opt | list, internally used option list.
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