Solver for the general p-quantile monotone regression problem with optional weights.
pSolver(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, aw and bw as quantile weights.
Details
This function is called internally in activeSet by setting mySolver = pSolver. Note that if aw = bw, we get the weighted median and therefore we solved the weighted absolute norm.
Returns
x: Vector containing the fitted values
lbd: Vector with Lagrange multipliers
f: Value of the target function
gx: Gradient at point x
References
Koenker, R. (2005). Quantile regression. Cambridge, MA: Cambridge University Press.
See Also
activeSet
Examples
##Fitting quantile regressionset.seed(12345)y <- rnorm(9)##response valuesw <- rep(1,9)##unit weightsbtota <- cbind(1:8,2:9)##Matrix defining isotonicity (total order)fit.p <- activeSet(btota, pSolver, weights = w, y = y, aw =0.3, bw =0.7)