lfSolver: General Least Squares Loss Function

Description Usage Arguments Details Value See Also Examples

View source: R/lfSolver.R

Description

Solver for the general least squares monotone regression problem of the form (y-x)'W(y-x).

Usage

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lfSolver(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 as weight matrix W which is not necessarily positive definite.

Details

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

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

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##Fitting isotone regression 
set.seed(12345)
y <- rnorm(9)              ##response values
w <- diag(rep(1,9))        ##unit weight matrix
btota <- cbind(1:8, 2:9)   ##Matrix defining isotonicity (total order)
#fit.lf <- activeSet(btota, lfSolver, weights = w, y = y)

isotone documentation built on May 29, 2017, 9:52 a.m.