pub struct Unbounded {
pub mean: Vec<f64>,
pub covariance: FlatMatrix,
}Expand description
The expected-information (Fisher scoring) expansion of the objective at
the fit over every free parameter, bounds left out: covariance F⁻¹, F
the expected information of all free parameters, and mean θ̂ − F⁻¹g, g
the objective’s gradient at the fit, which the convergence test makes
negligible off the bounds. Both are taken over the directions the counts
and priors determine; the mean and the rows and columns of a parameter
with a component along a direction they do not determine are NaN. With
none on a bound the covariance is PoissonResult::covariance.
Fields§
§mean: Vec<f64>§covariance: FlatMatrixTrait Implementations§
Auto Trait Implementations§
impl Freeze for Unbounded
impl RefUnwindSafe for Unbounded
impl Send for Unbounded
impl Sync for Unbounded
impl Unpin for Unbounded
impl UnsafeUnpin for Unbounded
impl UnwindSafe for Unbounded
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more