accessD.wd            package:wavethresh            R Documentation

_G_e_t _d_e_t_a_i_l (_m_o_t_h_e_r _w_a_v_e_l_e_t) _c_o_e_f_f_i_c_i_e_n_t_s _f_r_o_m _w_a_v_e_l_e_t _o_b_j_e_c_t (_w_d).

_D_e_s_c_r_i_p_t_i_o_n:

     This function extracts and returns a vector of mother wavelet
     coefficients, corresponding to a particular resolution level, from
     a 'wd' wavelet decomposition object.

     The pyramid of coefficients in a wavelet decomposition (returned
     from the 'wd' function, say) are packed into a single vector in
     WaveThresh.

_U_s_a_g_e:

     accessD.wd(wd, level, boundary=FALSE, aspect="Identity", ...)

_A_r_g_u_m_e_n_t_s:

      wd: Wavelet decomposition object from which you wish to extract
          the mother wavelet coefficients.

   level: The resolution level at which you wish to extract
          coefficients.

boundary: some methods of wavelet transform computation handle the
          boundaries by keeping some extra bookkeeping coefficients at
          either end of a resolution level. If this argument is TRUE
          then these bookkeeping coefficients are returned when the
          mother wavelets are returned. Otherwise, if FALSE, these
          coefficients are not returned.

  aspect: The aspect argument permits the user to supply a function to
          modify the returned coefficients. The function is applied to
          the vector of coefficients before it is returned. This can be
          useful, say, with the complex DWT where you could supply
          aspect="Mod" if you wanted to return the modulus of the
          coefficients at a given resolution level. The default
          argument, "Identity", ensures that the coefficients are not
          modified before returning.

     ...: any other arguments

_D_e_t_a_i_l_s:

     The need for this function is a consequence of the pyramidal
     structure of Mallat's algorithm and the memory efficiency gain
     achieved by storing the pyramid as a linear vector. AccessD
     obtains information about where the smoothed data appears from the
     'fl.dbase' component of an 'wd' object, in particular the array

     'fl.dbase$first.last.d'

     which gives a complete specification of index numbers and offsets
     for

     'wd.object$D'.

     Note that this function is a method for the generic function
     'accessD'. 

     Note also that this function only retrieves information from 'wd'
     class objects. To insert coefficients into 'wd' objects you have
     to use the 'putD' function (or more precisely, the 'putD.wd'
     method).

_V_a_l_u_e:

     A vector containing the mother wavelet coefficients at the
     required resolution level (the coefficients might have been
     modified depending on the value of the aspect argument).

_R_E_L_E_A_S_E:

     Version 3.5.3 Copyright Guy Nason 1994

_R_e_f_e_r_e_n_c_e_s:

     Mallat, S. G. (1989) A theory for multiresolution signal
     decomposition: the wavelet representation. _IEEE Transactions on
     Pattern Analysis and Machine Intelligence_. \bo1d{11}, 674-693. 

     Nason, G. P. and Silverman, B. W. (1994). The discrete wavelet
     transform in S. _Journal of Computational and Graphical
     Statistics_, *3*, 163-191

_S_e_e _A_l_s_o:

     'wr', 'wd', 'accessD', 'filter.select', 'threshold'

_E_x_a_m_p_l_e_s:

     #
     # Get the 4th resolution level of wavelet coefficients. 
     #
     #accessD(wd(data), level=4)
     #
     # Get the absolute value of the 7th level of complex wavelet coefficients
     #
     #my.wd <- wd(data, filter.number=3, family="Lawton")
     #accessD(my.wd, level=7, aspect="Mod")

