{"articles":{"fisher-scoring@computational-statistical-methods":{"content":"<p>Fisher scoring is a Newton-like method for maximizing a likelihood function where the Hessian stand-in is the negative Fisher information matrix, replacing the negative observed information \\({-{\\sum}_{i} {{\\partial}_{\\theta}}^{2} \\ell(\\theta\\vert{x}_{i})}\\).</p>","names":[[["Fisher scoring",""]]]}},"style":"Method"}