Band-pass variance         package:waveslim         R Documentation

_B_a_n_d_p_a_s_s _V_a_r_i_a_n_c_e _f_o_r _L_o_n_g-_M_e_m_o_r_y _P_r_o_c_e_s_s_e_s

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

     Computes the band-pass variance for fractional difference (FD) or
     seasonal persistent (SP) processes using numeric integration of
     their spectral density function.

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

     bandpass.fdp(a, b, d)
     bandpass.spp(a, b, d, fG)
     bandpass.spp2(a, b, d1, f1, d2, f2)
     bandpass.var.spp(delta, fG, J, Basis, Length)

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

       a: Left-hand boundary for the definite integral.

       b: Right-hand boundary for the definite integral.

d,delta,d1,d2: Fractional difference parameter.

fG,f1,f2: Gegenbauer frequency.

       J: Depth of the wavelet transform.

   Basis: Logical vector representing the adaptive basis.

  Length: Number of elements in Basis.

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

     See references.

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

     Band-pass variance for the FD or SP process between a and b.

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

     B. Whitcher

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

     McCoy, E. J., and A. T. Walden (1996) Wavelet analysis and
     synthesis of stationary long-memory processes, _Journal for
     Computational and Graphical Statistics_, *5*, No. 1, 26-56.

     Whitcher, B. (2001) Simulating Gaussian stationary processes with
     unbounded spectra, _Journal for Computational and Graphical
     Statistics_, *10*, No. 1, 112-134.

