Parameters : | x : array_like
Input data for regression.
y : array_like, optional
Input data for regression.
we : array_like, optional
If we is a scalar, then that value is used for all data points (and
all dimensions of the response variable).
If we is a rank-1 array of length q (the dimensionality of the
response variable), then this vector is the diagonal of the covariant
weighting matrix for all data points.
If we is a rank-1 array of length n (the number of data points), then
the i’th element is the weight for the i’th response variable
observation (single-dimensional only).
If we is a rank-2 array of shape (q, q), then this is the full
covariant weighting matrix broadcast to each observation.
If we is a rank-2 array of shape (q, n), then we[:,i] is the
diagonal of the covariant weighting matrix for the i’th observation.
If we is a rank-3 array of shape (q, q, n), then we[:,:,i] is the
full specification of the covariant weighting matrix for each
observation.
If the fit is implicit, then only a positive scalar value is used.
wd : array_like, optional
If wd is a scalar, then that value is used for all data points
(and all dimensions of the input variable). If wd = 0, then the
covariant weighting matrix for each observation is set to the identity
matrix (so each dimension of each observation has the same weight).
If wd is a rank-1 array of length m (the dimensionality of the input
variable), then this vector is the diagonal of the covariant weighting
matrix for all data points.
If wd is a rank-1 array of length n (the number of data points), then
the i’th element is the weight for the i’th input variable observation
(single-dimensional only).
If wd is a rank-2 array of shape (m, m), then this is the full
covariant weighting matrix broadcast to each observation.
If wd is a rank-2 array of shape (m, n), then wd[:,i] is the
diagonal of the covariant weighting matrix for the i’th observation.
If wd is a rank-3 array of shape (m, m, n), then wd[:,:,i] is the
full specification of the covariant weighting matrix for each
observation.
fix : array_like of ints, optional
The fix argument is the same as ifixx in the class ODR. It is an
array of integers with the same shape as data.x that determines which
input observations are treated as fixed. One can use a sequence of
length m (the dimensionality of the input observations) to fix some
dimensions for all observations. A value of 0 fixes the observation,
a value > 0 makes it free.
meta : dict, optional
Freeform dictionary for metadata.
|