 Orthogonalization equation for two statistical parameters

Write the old nuisance parameter as $\lambda =g(\psi ,\eta )$ with $g_{\eta }\ne 0$. The transformed score functions are $u_{\psi }^{\mathrm{new}}=u_{\psi }+g_{\psi }{u}_{\lambda }$ and $u_{\eta }=g_{\eta }{u}_{\lambda }$. Their expected cross product is $g_{\eta }(I_{\psi \lambda }+g_{\psi }{I}_{\lambda \lambda })$. Setting it to zero gives the displayed ordinary differential equation along fixed-$\eta$ curves, assuming positive nuisance Fisher information. Smooth solutions with distinct initial conditions give a local interest-respecting orthogonal coordinate system.