Usage: |
{m,b,bv,const} = gintestpl(code,x,t,y,h,g{,opt})
|
Input: |
| code | text string, the short code for the model (e.g.
"bilo" for logit or "noid" for ordinary PLM),
see tutorial.
|
| x | n x d matrix, the discrete predictor variables.
|
| t | n x p matrix, the continuous predictor variables.
|
| y | n x 1 vector, the response variables.
|
| h | p x 1 vector or scalar, chosen bandwidth for
the directions of interest.
|
| g | p x 1 vector or scalar, chosen bandwidth for
the directions not of interest.
|
| opt | optional, a list with optional input. The quantlet
"gamopt" can be used to set up this parameter.
The order of the list elements is not important.
|
| opt.tg | ng x 1 vector, a grid for continuous part. If tg is
given, the nonparametric function will also be
computed on this grid.
|
| opt.wx | scalar or n x 1 vector, prior weights. For
binomial models usually the binomial index vector.
If not given, set to 1.
|
| opt.b0 | d x 1 vector, the initial coefficients. If not
given, all coefficients are set to GLM pre-estimation.
|
| opt.wt | n x 1 vector, weights for t (trimming factors).
If not given, all set to 1.
|
| 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.nosort | integer, if exists and =1, the continuous variables
t and the grid tg are assumed to be sorted by the
1st column. Sorting is required by the algorithm,
hence you should switch if off only when the data
are already sorted.
|
| opt.miter | integer, maximal number of iterations. The default
is 10.
|
| opt.cnv | integer, convergence criterion. The default is 0.0001.
|
| opt.fscor | integer, if exists and =1, a Fisher scoring is
performed (instead of the default Newton-Raphson
procedure). This parameter is ignored for
canonical links.
|
| opt.wtc | n x 1 vector, weights for convergence criterion,
w.r.t. m(t) only. If not given, opt.wt is used.
|
| opt.off | scalar or n x 1 vector, offset. Can be used for
constrained estimation. If not given, set to 0.
|
| opt.pow | scalar, power for power link. If not given,
set to 0.
|
| opt.nbk | scalar, extra parameter k for negative binomial
distribution. If not given, set to 1 (geometric
distribution).
|
Output: |
| m | n x 1 vector, estimated nonparametric part |
| b | d x 1 vector, estimated coefficients |
| bv | d x d matrix, estimated covariance matrix for coeff. |
| const | ng x 1 vector, estimated nonparametric part on grid |