  We pursue the development and application of the recently-introduced linear
optimization method for determining the optimal linear and nonlinear parameters
of Jastrow-Slater wave functions in a variational Monte Carlo framework. In
this approach, the optimal parameters are found iteratively by diagonalizing
the Hamiltonian matrix in the space spanned by the wave function and its
first-order derivatives, making use of a strong zero-variance principle. We
extend the method to optimize the exponents of the basis functions,
simultaneously with all the other parameters, namely the Jastrow, configuration
state function and orbital parameters. We show that the linear optimization
method can be thought of as a so-called augmented Hessian approach, which helps
explain the robustness of the method and permits us to extend it to minimize a
linear combination of the energy and the energy variance. We apply the linear
optimization method to obtain the complete ground-state potential energy curve
of the C_2 molecule up to the dissociation limit, and discuss size consistency
and broken spin-symmetry issues in quantum Monte Carlo calculations. We perform
calculations of the first-row atoms and homonuclear diatomic molecules with
fully optimized Jastrow-Slater wave functions, and we demonstrate that
molecular well depths can be obtained with near chemical accuracy quite
systematically at the diffusion Monte Carlo level for these systems.
