eSolver: L1 approximation

In isotone: Active Set and Generalized PAVA for Isotone Optimization

L1 approximation

Description

Solves an L1 approximation.

Usage

eSolver(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, eps for the error term

Details

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

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
eps = 0.01                 ##error term
btota <- cbind(1:8, 2:9)   ##Matrix defining isotonicity (total order)
fit.approx <- activeSet(btota, eSolver, weights = w, y = y, eps = eps)

isotone documentation built on March 7, 2023, 3:17 p.m.