parabolaSlopes           package:stinepack           R Documentation

_E_s_t_i_m_a_t_e _t_h_e _s_l_o_p_e _o_f _a_n _i_n_t_e_r_p_o_l_a_t_i_n_g _f_u_n_c_t_i_o_n _u_s_i_n_g _a _p_a_r_a_b_o_l_a

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

     Returns estimates of the slope of an interpolating function that 
     runs through a set of points in the xy-plane.

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

      
          parabolaSlopes(x,y)

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

     x,y: coordinates of points defining the interpolating function.

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

     Returns an estimate of the slope of the interpolant at (x,y).

_N_o_t_e:

     This function is used as part of the Stineman interpolation
     function 'stinterp'.  It is rarely called directly by the user, 
     and checking of x and y must be performed by the calling function.

     The parabola method provides a better approximation of the slope
     for smooth functions than the original method suggested by
     Stineman (1980), which is provided by the function
     'stinemanSlopes' (see the documentation  of the function
     'stinterp' for further information),  but it results in higher
     slopes near abrupt steps or spikes  and can lead to some
     overshooting where Stineman's method does not.

_A_u_t_h_o_r(_s):

     Norbert Nemec, Institute of Theoretical Physics, University of
     Regensburg. Translation from Python code by  Halldor Bjornsson

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

     'stinterp' and 'stinemanSlopes'.

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

     x <- seq(0,2*pi,by=pi/6)
     y <- sin(x)
     ## Not run: parabolaSlopes(x,y)

