lfSolver function

General Least Squares Loss Function

Solver for the general least squares monotone regression problem of the form (y-x)'W(y-x).

lfSolver(z, a, extra)

Arguments

• z: Vector containing observed response

• a: Matrix with active constraints

• extra: List with element y containing the observed response vector and weights

  as weight matrix W which is not necessarily positive definite.

Details

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

Returns

• x: Vector containing the fitted values

• lbd: Vector with Lagrange multipliers

• f: Value of the target function

• gx: Gradient at point x

See Also

activeSet

Examples

##Fitting isotone regression 
set.seed(12345)
y <- rnorm(9)              ##response values
w <- diag(rep(1,9))        ##unit weight matrix
btota <- cbind(1:8, 2:9)   ##Matrix defining isotonicity (total order)
#fit.lf <- activeSet(btota, lfSolver, weights = w, y = y)