public static class Gaussian.Parametric extends java.lang.Object implements ParametricUnivariateFunction
Constructor and Description |
---|
Parametric() |
Modifier and Type | Method and Description |
---|---|
double[] |
gradient(double x,
double... param)
Computes the value of the gradient at
x . |
private void |
validateParameters(double[] param)
Validates parameters to ensure they are appropriate for the evaluation of
the
value(double,double[]) and gradient(double,double[])
methods. |
double |
value(double x,
double... param)
Computes the value of the Gaussian at
x . |
public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
x
.value
in interface ParametricUnivariateFunction
x
- Value for which the function must be computed.param
- Values of norm, mean and standard deviation.NullArgumentException
- if param
is null
.DimensionMismatchException
- if the size of param
is
not 3.NotStrictlyPositiveException
- if param[2]
is negative.public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
x
.
The components of the gradient vector are the partial
derivatives of the function with respect to each of the
parameters (norm, mean and standard deviation).gradient
in interface ParametricUnivariateFunction
x
- Value at which the gradient must be computed.param
- Values of norm, mean and standard deviation.x
.NullArgumentException
- if param
is null
.DimensionMismatchException
- if the size of param
is
not 3.NotStrictlyPositiveException
- if param[2]
is negative.private void validateParameters(double[] param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
value(double,double[])
and gradient(double,double[])
methods.param
- Values of norm, mean and standard deviation.NullArgumentException
- if param
is null
.DimensionMismatchException
- if the size of param
is
not 3.NotStrictlyPositiveException
- if param[2]
is negative.