aSolver: Asymmetric Least Squares

Description Usage Arguments Details Value References See Also Examples

View source: R/aSolver.R

Description

Minimizes Efron's asymmetric least squares regression.

Usage

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aSolver(z, a, extra)

Arguments

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

Details

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

Value

x

Vector containing the fitted values

lbd

Vector with Lagrange multipliers

f

Value of the target function

gx

Gradient at point x

References

Efron, B. (1991). Regression percentiles using asymmetric squared error loss. Statistica Sinica, 1, 93-125.

See Also

activeSet

Examples

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##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.asy <- activeSet(btota, aSolver, weights = w, y = y, aw = 0.3, bw = 0.5)

isotone documentation built on May 2, 2019, 4:41 p.m.