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.