bkfe               package:KernSmooth               R Documentation

_C_o_m_p_u_t_e _a _B_i_n_n_e_d _K_e_r_n_e_l _F_u_n_c_t_i_o_n_a_l _E_s_t_i_m_a_t_e

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

     Returns an estimate of a binned approximation to the kernel
     estimate of the specified density functional.  The kernel is the
     standard normal density.

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

     bkfe(x, drv, bandwidth, gridsize=401, range.x=range(x),
          binned=FALSE, truncate=FALSE)

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

       x: vector of observations from the distribution whose density is
          to be estimated. Missing values are not allowed. 

     drv: order of derivative in the density functional. Must be a
          non-negative even integer. 

bandwidth: the kernel bandwidth smoothing parameter. 

gridsize: the number of equally-spaced points over which binning is
          performed. 

 range.x: vector containing the minimum and maximum values of `x' at
          which to compute the estimate. The default is the minimum and
          maximum data values. 

  binned: logical flag: if `TRUE', then `x' and `y' are taken to be
          grid counts rather than raw data. 

truncate: logical flag: if `TRUE', data with `x' values outside the
          range specified by `range.x' are ignored. 

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

     The density functional of order `drv' is the integral of the
     product of the density and its `drv'th derivative.  The kernel
     estimates of such quantities are computed using a binned
     implementation, and the kernel is the standard normal density.

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

     the estimated functional.

_B_a_c_k_g_r_o_u_n_d:

     Estimates of this type were proposed by Sheather and Jones (1991).

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

     Sheather, S. J. and Jones, M. C. (1991). A reliable data-based
     bandwidth selection method for kernel density estimation. Journal
     of the Royal Statistical Society, Series B, 53, 683-690.

     Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and
     Hall, London.

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

     data(geyser)
     x <- geyser$duration
     est <- bkfe(x, drv=4, bandwidth=0.3)

