Usage: |
{b,bv,df,m,mg,it}
= gplmcore(code,x,t,y,h,wx,wt,wc,b0,m0,ctrl{,upb{,tg,m0g}})
|
Input: |
| code | text string, the short code for the model (e.g.
"bilo" for logit or "noid" for ordinary PLM).
|
| x | n x p matrix, the discrete predictor variables.
|
| t | n x q matrix, the continuous predictor variables.
Needs to be SORTED by the first column.
|
| y | n x d vector, the response variables.
|
| h | q x 1 vector, the bandwith.
|
| wx | n x 1 vector or scalar, prior weights, e.g. the
binomial index vector.
|
| wt | n x 1 vector or scalar, weights for t (trimming
factors). Is ignored, when scalar.
|
| wc | n x 1 vector or scalar, weights for convergence
criterion, w.r.t. m(t) only. Is ignored, when scalar.
|
| b0 | p x 1 vector, the initial coefficients.
|
| m0 | n x 1 vector or scalar, the initial values for the
nonparametric part. Is ignored and can be set to
scalar direct update for nonparametric function is
possible (code="noid").
|
| off | n x 1 vector or scalar, offset. Is ignored when 0.
|
| ctrl | 7 x 1 vector or scalar, contains control parameters
shf (default=0),
miter (default=10),
cnv (default=0.0001),
fscor (default=0),
pow (default=0, power for power link),
nbk (default=1, parameter for negative binomial),
meth (default=0, parameter for backfitting/profile).
Alternatively, one can give here shf only. Set to 0
to use the defaults.
The parameters correspond to the optional parameters
which can be given in gplminit.
They are all ignored when not applicable.
|
| upb | optional, scalar, 0 or 1 (default). If set to
0, the parameter b is not updated in the
iteration.
|
| tg | optional, ng x 1 vector, a grid for continuous part.
Needs to be SORTED by the first column. Is ignored,
if set to NaN.
|
| m0g | optional, ng x 1 vector or scalar, the initial values
for the nonparametric part on the grid. Needs to be
given if direct update for nonparametric function
is not possible. Is ignored otherwise. Is ignored,
if tg set to NaN.
|
Output: |
| b | p x 1 vector, estimated coefficients |
| bv | p x p matrix, estimated covariance matrix for coeff. |
| m | n x 1 vector, estimated nonparametric part. |
| df | scalar, approximated degrees of freedom. |
| mg | ng x 1 vector, estimated nonparametric part on grid.
Only available if tg was given. |
| it | integer, number of iterations needed. |
| ret | scalar, return code:
0 o.k.,
1 maximal number of iterations reached
(if applicable),
-1 missing values have been encountered. |