eSolver: L1 approximation
In isotone: Active Set and Generalized PAVA for Isotone Optimization

Description Usage Arguments Details Value See Also Examples

Solves an L1 approximation.

1	eSolver(z, a, extra)

`z`	Vector containing observed response
`a`	Matrix with active constraints
`extra`	List with element `y` containing the observed response vector and `weights` with optional observation weights, `eps` for the error term

This function is called internally in activeSet by setting mySolver = eSolver.

`x`	Vector containing the fitted values
`lbd`	Vector with Lagrange multipliers
`f`	Value of the target function
`gx`	Gradient at point x

activeSet

##Fitting isotone regression using active set
set.seed(12345)
y <- rnorm(9)              ##response values
w <- rep(1,9)              ##unit weights
eps = 0.01                 ##error term
btota <- cbind(1:8, 2:9)   ##Matrix defining isotonicity (total order)
fit.approx <- activeSet(btota, eSolver, weights = w, y = y, eps = eps)