Modifier and Type | Class and Description |
---|---|
class |
GeneralizedLinearModel
The Generalized Linear Model (GLM) is a flexible generalization of the Ordinary Least Squares
regression.
|
Modifier and Type | Class and Description |
---|---|
class |
GeneralizedLinearModelQuasiFamily
GLM for the quasi-families.
|
Modifier and Type | Class and Description |
---|---|
class |
ConstrainedLASSObyLARS
This class solves the constrained form of LASSO by modified least angle regression (LARS) and
linear interpolation:
\[
\min_w \left \{ \left \| Xw - y \right \|_2^2 \right \}\) subject to \( \left \| w \right \|_1
\leq t
\]
|
class |
ConstrainedLASSObyQP
This class solves the constrained form of LASSO (i.e.\(\min_w \left \{ \left \| Xw - y \right
\|_2^2 \right \}\)
subject to \( \left \| w \right \|_1 \leq t \)) by transforming it into a single quadratic
programming problem with (2 * m + 1) constraints, where m is the number of
columns of the design matrix.
|
class |
UnconstrainedLASSObyCoordinateDescent
This class solves the unconstrained form of LASSO, that is,
\[
\min_w \left \{ \left \| Xw - y \right \|_2^2 + \lambda * \left \| w
\right \|_1 \right \}
\]
by Coordinate Descent method.
|
class |
UnconstrainedLASSObyQP
This class solves the unconstrained form of LASSO
(i.e.
|
Modifier and Type | Class and Description |
---|---|
class |
LogisticRegression
A logistic regression (sometimes called the logistic model or logit model) is used for prediction
of the probability of occurrence of an event by fitting data to a logit function logistic curve.
|
Modifier and Type | Class and Description |
---|---|
class |
OLSRegression
(Weighted) Ordinary Least Squares (OLS) is a method for fitting a linear regression model.
|
Modifier and Type | Method and Description |
---|---|
LinearModel |
PanelRegression.getLinearModel(Object subject)
Gets the linear model for a particular subject/individual.
|
LinearModel |
FixedEffectsModel.getLinearModel(Object subject) |
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