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 = 401L, range.x, binned = FALSE, truncate = TRUE) _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. Must be supplied. 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, extended by the support of the kernel. 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 (scalar) 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, package="MASS") x <- geyser$duration est <- bkfe(x, drv=4, bandwidth=0.3)