lsSolver {isotone}

Least Squares Loss Function

Description

Solver for the least squares monotone regression problem with optional weights.

Usage

lsSolver(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 with optional observation weights

Details

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

Value

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 using active set
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.ls <- activeSet(btota, lsSolver, weights = w, y = y)