  Iterative methods for nonlinear monotone equations do not require the
differentiability assumption on the residual function. This special property of
the methods makes them suitable for solving large-scale nonsmooth monotone
equations. In this work, we present a diagonal Polak-Ribeire-Polyk (PRP)
conjugate gradient-type method for solving large-scale nonlinear monotone
equations with convex constraints. The search direction is a combine form of a
multivariate (diagonal) spectral method and a modified PRP conjugate gradient
method. Proper safeguards are devised to ensure positive definiteness of the
diagonal matrix associated with the search direction. Based on Lipschitz
continuity and monotonicity assumptions the method is shown to be globally
convergent. Numerical results are presented by means of comparative experiments
with a recently proposed multivariate spectral conjugate gradient-type method.
