stopping_condition: Stopping conditions in iterative methods
In brunasqz/NonlinearOpMethods: Nonlinear Optimization Methods

Description Usage Arguments Value Examples

stopping_conditions is a function used in iterative methods for stopping the process when the conditions are fulfilled. These conditions are stabilization of the function value, reduction of the gradient norm to a value less than epsilon and maximum number of evaluation of objective funtion.

1	stopping_condition(x.k1, x.k, eps.f = 1e-09, eps.df = 1e-08)

`x.k1`	A list that contains the information of the point in current iterantion. It must have the names x: a vector with its value in the search space fx: a scalar with its objective value dfx: a vector with its gradient value
`x.k`	A list that contains the information of the point in current iterantion, in the same pattern as `x_k1`.
`eps.f`	A number for minimum variation of the objective function in the iterations.
`eps.df`	A number for minimum variation of the gradient in the iterations.

Returns a results of boolean algebra.

## Not run: 
x1 <- list(x = c(1,1), fx = 12, dfx = c(-1,2))
xk <- list(x = c(0.008, 1.01), fx = 11.00009, dfx = c(-0.9999, 2.9999))
stopping_condition(x1, xk, eps.f = 1e-9, eps.df = 1e-8)

## End(Not run)