qbsks                  package:cobs                  R Documentation

_Q_u_a_n_t_i_l_e _B-_S_p_l_i_n_e _w_i_t_h _F_i_x_e_d _K_n_o_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Compute B-spline coefficients for regression quantile B-spline
     with stepwise knots selection and quantile B-spline with fixed
     knots *regression spline*, using Ng (1996)'s algorithm.

_U_s_a_g_e:

     qbsks(x,y,w,pw, knots,nknots, degree,Tlambda, constraint,
           n.sub = n1000cut(n), equal,smaller, greater,gradient, coef,maxiter,
           trace, n.equal,n.smaller,n.greater,n.gradient,
           nrq,nl1, neqc, nj0, tau,lam,tmin,kmax,lstart,
           ks,mk.flag, knots.add, ic, print.mesg,
           factor, tol.kn = 1e-6, eps = .Machine$double.eps, print.warn)

_A_r_g_u_m_e_n_t_s:

       x: numeric vector, sorted increasingly, the abscissa values

       y: numeric, same length as 'x', the observations.

       w: numeric vector of weights, same length as 'x', as in 'cobs'.

      pw: penalty weights vector ... ...

   knots: ~~Describe 'knots' here~~ 

  nknots: ~~Describe 'nknots' here~~ 

  degree: integer specifying polynomial degree; must be 1 or 2.

 Tlambda: ~~Describe 'Tlambda' here~~ 

constraint: ~~Describe 'constraint' here~~ 

   n.sub: integer, not larger than sample size 'n'; the default has
          'n.sub == n' as long as 'n' is less than 1000.

   equal: ~~Describe 'equal' here~~ 

 smaller: ~~Describe 'smaller' here~~ 

 greater: ~~Describe 'greater' here~~ 

gradient: ~~Describe 'gradient' here~~ 

    coef: ~~Describe 'coef' here~~ 

 maxiter: ~~Describe 'maxiter' here~~ 

   trace: ~~Describe 'trace' here~~ 

 n.equal: ~~Describe 'n.equal' here~~ 

n.smaller: ~~Describe 'n.smaller' here~~ 

n.greater: ~~Describe 'n.greater' here~~ 

n.gradient: ~~Describe 'n.gradient' here~~ 

     nrq: ~~Describe 'nrq' here~~ 

     nl1: ~~Describe 'nl1' here~~ 

    neqc: ~~Describe 'neqc' here~~ 

     nj0: ~~Describe 'nj0' here~~ 

     tau: ~~Describe 'tau' here~~ 

     lam: ~~Describe 'lam' here~~ 

    tmin: ~~Describe 'tmin' here~~ 

    kmax: ~~Describe 'kmax' here~~ 

  lstart: ~~Describe 'lstart' here~~ 

      ks: ~~Describe 'ks' here~~ 

 mk.flag: ~~Describe 'mk.flag' here~~ 

knots.add: ~~Describe 'knots.add' here~~ 

      ic: ~~Describe 'ic' here~~ 

print.mesg: ~~Describe 'print.mesg' here~~ 

  factor: ~~Describe 'factor' here~~ 

  tol.kn: ``tolerance'' for shifting the outer knots.

     eps: tolerance passed to 'drqssbc'.

print.warn: flag indicating if and how much warnings and information is
          to be printed;  currently just passed to 'drqssbc'.

_D_e_t_a_i_l_s:

     This is an auxiliary function for 'cobs(*, lambda = 0)', possibly
     interesting on its own.  This documentation is currently sparse;
     read the source code!

_V_a_l_u_e:

     a list with components 

    coef: ..

   fidel: ..

       k: dimensionality of model fit.

     ifl: integer ``flag''; the return code.

    icyc: integer of length 2, see 'cobs'.

   knots: the vector of inner knots.

  nknots: the number of inner knots.

    nvar: the number of ``variables'', i.e. unknowns including
          constraints.

  lambda: the penalty factor, chosen or given.

pseudo.x: the pseudo design matrix X, as returned from 'drqssbc'.

_A_u_t_h_o_r(_s):

     Pin Ng; this help page: Martin Maechler.

_R_e_f_e_r_e_n_c_e_s:

     Ng, P. (1996) An Algorithm for Quantile Smoothing Splines,
     _Computational Statistics & Data Analysis_ *22*, 99-118.

_S_e_e _A_l_s_o:

     the main function 'cobs'; further 'drqssbc' which is called from
     'qbsks()'.

_E_x_a_m_p_l_e_s:

