| fSolver | R Documentation | 
Specification of a differentiable convex loss function.
fSolver(z, a, extra)
z | 
 Vector containing observed response  | 
a | 
 Matrix with active constraints  | 
extra | 
 List with element   | 
This function is called internally in activeSet by setting mySolver = fSolver. It uses
optim() with "BFGS" for optimization.
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 (L2-norm user-specified)
set.seed(12345)
y <- rnorm(9)              ##response values
w <- rep(1,9)              ##unit weights
btota <- cbind(1:8, 2:9)   ##Matrix defining isotonicity (total order)
fit.convex <- activeSet(btota, fSolver, fobj = function(x) sum(w*(x-y)^2), 
gobj = function(x) 2*drop(w*(x-y)), y = y, weights = w)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.