Function lstsq::lstsq

pub fn lstsq<R, M, N>(
    a: &OMatrix<R, M, N>,
    b: &OVector<R, M>,
    epsilon: R
) -> Result<Lstsq<R, N>, &'static str>
where
    R: RealField,
    M: DimMin<N>,
    N: Dim,
    DimMinimum<M, N>: DimSub<U1>,
    DefaultAllocator: Allocator<R, M, N> + Allocator<R, N> + Allocator<R, M> + Allocator<R, DimDiff<DimMinimum<M, N>, U1>> + Allocator<R, DimMinimum<M, N>, N> + Allocator<R, M, DimMinimum<M, N>> + Allocator<R, DimMinimum<M, N>> + Allocator<(usize, usize), DimMinimum<M, N>> + Allocator<(R, usize), DimMinimum<M, N>>,

Return the least-squares solution to a linear matrix equation.

Computes the vector x that approximatively solves the equation a * x = b. Usage is maximally compatible with Python’s numpy.linalg.lstsq.

Arguments:

• a: “Coefficient” matrix (shape: M rows, N columns)
• b: Ordinate or “dependent variable” values (shape: M dimensional)
• epsilon: singular values less than this are assumed to be zero.

Returns:

• Result<Lstsq,&'static str>

See the module level documentation for example of usage.