lsSolver {isotone} | R Documentation |
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)
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.ls <- activeSet(z, btota, lsSolver, weights = w, y = y)
[Package
isotone version 0.8-1
Index]