aSolver {isotone} | R Documentation |
Minimizes Efron's asymmetric least squares regression.
aSolver(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, weight aw for y > x, and weight bw for y <= x |
This function is called internally in activeSet
by setting mySolver = aSolver
.
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 btota <- cbind(1:8, 2:9) ##Matrix defining isotonicity (total order) fit.asy <- activeSet(z, btota, aSolver, weights = w, y = y, aw = 0.3, bw = 0.5)