compute_homoscedastic_outer_products

pyapprox.optimal_experimental_design.compute_homoscedastic_outer_products(factors)

Compute

\[f(x_i)f(x_i)^T\quad \forall i=0,\ldots,M\]

at a set of design pts \(x_i\).

for the linear model

\[y(x) = F(x)\theta+\eta(x)\epsilon\]

factorsnp.ndarray (M,N)

The N factors F of the linear model evaluated at the M design pts

Returns

homoscedastic_outer_productsnp.ndarray (N,N,M)

The outer products of each row of F with itself, i.e. \(f(x_i)f(x_i)^T\)