KernSmooth-internal        package:KernSmooth        R Documentation

_I_n_t_e_r_n_a_l _K_e_r_n_S_m_o_o_t_h _f_u_n_c_t_i_o_n_s

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

     Internal KernSmooth functions

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

     blkest(x, y, Nval, q)
     cpblock(X, Y, Nmax, q)
     linbin(X, gpoints, truncate=TRUE)
     linbin2D(X, gpoints1, gpoints2)
     rlbin(X, Y, gpoints, truncate=TRUE)
     sdiag(x, drv=0, degree=1, kernel="normal",
           bandwidth, gridsize=401, bwdisc=25, range.x,
           binned=FALSE, truncate=TRUE)
     sstdiag(x, drv=0, degree=1, kernel="normal",
             bandwidth, gridsize=401, bwdisc=25, range.x,
             binned=FALSE, truncate=TRUE)

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

     These are not to be called by the user.

     `blkest' is used to obtain preliminary estimates of quantities
     required for the ``direct plug-in'' regression bandwidth selector
     based on blocked qth degree polynomial fits.

     `cpblock' chooses the number of blocks for the preliminary step of
     a plug-in rule using Mallows' C_p.

     `linbin' applies linear binning to a univariate data set.

     `linbin2D' applies linear binning to a bivariate data set.

     `rlbin' applies linear binning to a regression data set.

     `sdiag' computes the binned diagonal entries of a smoother matrix
     for local polynomial kernel regression.

     `sstdiag' computes the binned diagonal entries of SS^T where S is
     a smoother matrix for local polynomial  kernel regression.

