EmpiricalHessian

Companion:
class
class Object
trait Matchable
class Any

Value members

Concrete methods

Calculate the Hessian using central differences

Calculate the Hessian using central differences

H_{i,j} = \lim_h -> 0 ((f'(x_{i} + he_{j}) - f'(x_{i} + he_{j}))/4h + (f'(x_{j} + he_{i}) - f'(x_{j} + he_{i}))/4h)

where e_{i} is the unit vector with 1 in the i^^th position and zeros elsewhere

Value parameters:
df

differentiable function

eps

a small value

x

the point we compute the hessian for

Returns:

Approximate hessian matrix

Implicits

Implicits

implicit def product[T, I]: Impl2[EmpiricalHessian[T], T, T]