On modified anti-Gaussian rules for Jacobi weight functions

Anti-Gaussian formulas represent an efficient tool for a dynamical estimation of the error of the underlying Gaussian rule. When applied to the Jacobi weight function it is known that such formulas are not always internal. In this work we show how to overcome this problem by using the so called modified anti-Gaussian rule with suitable parameter {\theta} = {\theta}(n), that depends on the number n of quadrature points of the Gaussian formula. Next we study theoretically the asymptotic rate of convergence of the corresponding modified averaged Gaussian formulas. We conclude by showing the benefits of this approach via numerical experiments. All the Matlab codes used in this work are available as open-source software.