pSolver function

Quantile Regression

Quantile Regression

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 regression 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.p <- activeSet(btota, pSolver, weights = w, y = y, aw = 0.3, bw = 0.7)