Description Usage Arguments Details Value References See Also
A localized version of multinomial regression.
1 2 |
formula |
A formula expression as for regression
models, of the form |
data |
An optional data frame in which to interpret
the variables occurring in |
subset |
An index vector specifying the cases to be used in the training sample. (NOTE: If given, this argument must be named.) |
na.action |
A function to specify the action to be
taken if NAs are found. The default action is first the
|
contrasts |
A list of contrasts to be used for some or all of the factors appearing as variables in the model formula. |
censored |
Logical. If the response is a matrix with
K > 2 classes, interpret the entries as one for
possible classes, zero for impossible classes. Defaults
to |
model |
Logical. If |
... |
Additional arguments for
|
This is a localized version of multinomial regression
where a multinomial regression model is fitted for each
test observation based on the training data near the
trial point. It is based on the function
multinom
from package nnet.
osnnet
is called internally.
In osmultinom
no fitting is done. In the
prediction step an individual model for every test
observation is fitted. Observations weights that reflect
the importance of training observations for the fit at a
particular test observation are calculated internally in
predict.osmultinom
. For this reason not all
types of response in formula
are allowed and
osmultinom
does not take all arguments that can be
passed to multinom
. As response in
formula
factors and matrices are allowed. If
censored = FALSE
only zero-one class indicator
matrices are allowed. Argument weights
is missing
since observations weights are calculated internally in
predict.osmultinom
. summ
that
specifies a method to summarize rows of the model matrix
is missing since this requires adjustment of the case
weights. Also Hess
is not supported.
An object of class osmultinom
, inheriting from
"osnnet"
, a list
containing the following
components:
x |
A |
y |
If argument |
... |
|
mask |
The |
maxit |
The |
trace |
The |
abstol |
The |
reltol |
The |
lev |
If |
wf |
The window function used. Always a function, even if the input was a string. |
bw |
(Only if |
k |
(Only if |
nn.only |
(Logical. Only if |
adaptive |
(Logical.)
|
variant |
(Only if |
call |
The (matched) function call. |
Czogiel, I., Luebke, K., Zentgraf, M. and Weihs, C. (2007), Localized linear discriminant analysis. In Decker, R. and Lenz, H.-J., editors, Advances in Data Analysis, volume 33 of Studies in Classification, Data Analysis, and Knowledge Organization, pages 133–140, Springer, Berlin Heidelberg.
Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
predict.osmultinom
, osnnet
,
nnet
.
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