iSolver {isotone} | R Documentation |
Minimizes soft insensitive loss function (SILF) for support vector regression.
iSolver(z, a, extra)
z |
Vector containing observed response |
a |
Matrix with active constraints |
extra |
List with element y containing the observed response vector, weights
with optional observation weights, beta between 0 and 1, and eps > 0 |
This function is called internally in activeSet
by setting mySolver = iSolver
.
x |
Vector containing the fitted values |
lbd |
Vector with Lagrange multipliers |
f |
Value of the target function |
gx |
Gradient at point x |
Efron, B. (1991). Regression percentiles using asymmetric squared error loss. Statistica Sinica, 1, 93-125.
##Fitting isotone regression using active set set.seed(12345) z <- 9:1 ##predictor values y <- rnorm(9) ##response values w <- rep(1,9) ##unit weights eps <- 2 beta <- 0.4 btota <- cbind(1:8, 2:9) ##Matrix defining isotonicity (total order) fit.silf <- activeSet(z, btota, iSolver, weights = w, y = y, beta = beta, eps = eps)