rbox                 package:locfit                 R Documentation

_L_o_c_a_l _R_e_g_r_e_s_s_i_o_n, _L_i_k_e_l_i_h_o_o_d _a_n_d _D_e_n_s_i_t_y _E_s_t_i_m_a_t_i_o_n.

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

     'rbox()' is used to specify a rectangular box evaluation structure
     for 'locfit.raw()'. The structure begins by generating a bounding
     box for the data, then recursively divides the box to a desired
     precision.

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

     rbox(cut=0.8, type="tree", ll, ur)

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

    type: If 'type="tree"', the cells are recursively divided according
          to the bandwidths at each corner of the cell; see Chapter 11
          of Loader (1999). If 'type="kdtree"', the K-D tree structure
          used in Loess (Cleveland and Grosse, 1991) is used. 

     cut: Precision of the tree; a smaller value of 'cut' results in a
          larger tree with more nodes being generated. 

      ll: Lower left corner of the initial cell. Length should be the
          number of dimensions of the data provided to 'locfit.raw()'. 

      ur: Upper right corner of the initial cell. By default, 'll' and
          'ur' are generated as the bounding box for the data. 

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

     Loader, C. (1999). Local Regression and Likelihood. Springer, New
     York.

     Cleveland, W. and Grosse, E. (1991). Computational Methods for
     Local Regression. Statistics and Computing 1.

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

     data(ethanol, package="locfit")
     plot.eval(locfit(NOx~E+C,data=ethanol,scale=0,ev=rbox(cut=0.8)))
     plot.eval(locfit(NOx~E+C,data=ethanol,scale=0,ev=rbox(cut=0.3)))

