iregnet_compute_gradients: Compute the gradients of the log Likelihood wrt beta, and...
In anujkhare/iregnet: Regularized interval regression
Description
C++ function to compute the gradients of log likelihood with respect to the
coefficients beta and scale.
The supported distributions are gaussian,
logistic and (least) extreme value.
This is used for testing, and may not be useful otherwise.
Usage
1
iregnet_compute_gradients(X, y, eta, scale, family)
Arguments
X
Design matrix.
y
Output matrix in 2 column format.
eta
Linear predictors.
scale
Scale.
family
The distribution of the data. Guassian, logistic and
(least) extreme value distributions are supported.
anujkhare/iregnet documentation built on Aug. 23, 2019, 8:24 p.m.
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Description
C++ function to compute the gradients of log likelihood with respect to the
coefficients beta and scale.
The supported distributions are gaussian,
logistic and (least) extreme value.
This is used for testing, and may not be useful otherwise.
Usage
1 | iregnet_compute_gradients(X, y, eta, scale, family)
|
Arguments
X |
Design matrix. |
y |
Output matrix in 2 column format. |
eta |
Linear predictors. |
scale |
Scale. |
family |
The distribution of the data. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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