Description Usage Arguments Details Value Author(s) References See Also Examples
Estimate the Bspline coefficients for a regression quantile smoothing spline with optional constraints, using Ng(1996)'s algorithm.
1 2 3 4 5 6 7 8 9  drqssbc(x, y, w= rep(1,n), pw, knots, degree, Tlambda, constraint,
n.sub = n1000cut(nrq),
equal, smaller, greater, gradient, coef, maxiter = 20 * n,
trace = 1,
n.equal = nrow(equal), n.smaller = nrow(smaller),
n.greater = nrow(greater), n.gradient = nrow(gradient),
nrq = length(x), nl1, neqc, niqc, nvar, nj0,
tau = 0.5, lam, tmin, kmax, lstart, factor,
eps = .Machine$double.eps, print.warn)

x 
numeric vector, sorted increasingly, the abscissa values 
y 
numeric, same length as 
w 
numeric vector of weights, same length as 
pw 
penalty weights vector passed to 
knots 
numeric vector of knots for the splines. 
degree 
integer, must be 1 or 2. 
Tlambda 
vector of smoothing parameter values λ; if it is longer than one, an “optimal” value will be selected from these. 
constraint 
see 
n.sub 
integer, not larger than sample size 
equal,smaller, greater 
3column matrices specifying the respective constraints. The has 0 zeros if there no constraints of the corresponding kind. 
gradient 
3column matrix for gradient constraints. 
coef 
numeric vector, the initial guess for the Bspline coefficients. 
maxiter 
upper bound of the number of iteration; default to 20*n. 
trace 
integer or logical indicating the tracing level of the underlying algorithms; not much implemented (due to lack of trace in quantreg ..). 
n.equal,n.smaller,n.greater,n.gradient 
integers, each specifying the corresponding number of constraints. 
nrq 
integer, = n, the number of observations. 
nl1 
integer, number of observations in the l1 norm that correspond to roughness measure (may be zero). 
neqc 
integer giving the number of equations. 
niqc 
integer giving the number of inequality
constraints; of the same length as 
nvar 
integer giving the number of equations and constraints. 
nj0 
integer; upper limit for the number of unique tau or lambda solutions. 
tau 
desired quantile level; defaults to 0.5 (median). 
lam 
initial λ value. 
tmin 
smallest value of tau to begin PLP in tau. 
kmax 
integer k_0, the largest effective dimension of the model allowed during PLP in lambda. 
lstart 
number, see 
factor 
number in [1,4], see 
eps 
tolerance used in the fortran code in many different contexts. 
print.warn 
logical indicating if warnings should be printed, when the algorithm seems to have behaved somewhat unexpectedly. 
This is an auxiliary function for cobs
, possibly
interesting on its own. This documentation is currently sparse; read
the source code!
a list with components ......
(use the cobs package instead!)
Pin Ng; this help page: Martin Maechler.
Ng, P. (1996) An Algorithm for Quantile Smoothing Splines, Computational Statistics \& Data Analysis 22, 99–118.
The main function cobs
and its auxiliary
qbsks
which calls drqssbc()
repeatedly.
1 2 3 4 5 
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