cdssden                 package:gss                 R Documentation

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

     Evaluate conditional pdf, cdf, and quantiles for smoothing spline
     density estimates.

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

     cdssden(object, x, cond, int=NULL)
     cpssden(object, q, cond, int=NULL)
     cqssden(object, p, cond, int=NULL)

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

  object: Object of class '"ssden"'.

       x: Data frame or vector of points on which conditional density
          is to be evaluated.

    cond: One row data frame of conditioning variables.

     int: Normalizing constant.

       q: Vector of points on which conditional cdf is to be evaluated.

       p: Vector of probabilities for which conditional quantiles are
          to be calculated.

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

     The argument 'x' in 'cdssden' is of the same form as the argument
     'newdata' in 'predict.lm', but can take a vector for 1-D
     conditional densities.

     'cpssden' and 'cqssden' naturally only work for 1-D conditional
     densities of a numerical variable.

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

     'cdssden' returns a list object with the following components. 

     pdf: Vector of conditional pdf.

     int: Normalizing constant.


     'cpssden' and 'cpssden' return a vector of conditional cdf or
     quantiles.

_N_o_t_e:

     If variables other than factors or numerical vectors are involved
     in 'x', the normalizing constant can not be computed.

     'cpssden' and 'cqssden' can be very slow.

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

     Fitting function 'ssden' and 'dssden'.

