fdSperio              package:fracdiff              R Documentation

_S_p_e_r_i_o _E_s_t_i_m_a_t_e _f_o_r '_d' _i_n _A_R_F_I_M_A(_p,_d,_q)

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

     This function makes use Reisen (1994) estimator to estimate the
     memory parameter d in the ARFIMA(p,d,q) model.  It is based on the
     regression equation using the smoothed peridogram function as an
     estimate of the spectral density.

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

     fdSperio(x, bandw.exp = 0.5, beta = 0.9)

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

       x: univariate time series data.

bandw.exp: numeric: exponent of the bandwidth used in the regression
          equation.

    beta: numeric: exponent of the bandwidth used in the lag Parzen
          window.

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

     The function also provides the asymptotic standard deviation and
     the standard error deviation of the fractional estimator.

     The bandwidths are 'bw = trunc(n ^ bandw.exp)', where 0 <
     bandw.exp < 1 and n is the sample size.  Default 'bandw.exp= 0.5'; 
      and 'bw2 = trunc(n ^ beta)', where 0 < beta < 1 and n is the
     sample size.  Default 'beta = 0.9'.

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

     a list with components 

       d: Sperio estimate

   sd.as: asymptotic standard deviation

  sd.reg: standard error deviation

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

     Valderio A. Reisen valderio@cce.ufes.br and Artur J. Lemonte

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

     Geweke, J. and Porter-Hudak, S. (1983) The estimation and
     application of long memory time series models. _Journal of Time
     Series Analysis_ *4*(4), 221-238.

     Reisen, V. A. (1994) Estimation of the fractional difference
     parameter in the ARFIMA(p,d,q) model using the smoothed
     periodogram. _Journal Time Series Analysis_, *15*(1), 335-350.

     Reisen, V. A., B. Abraham, and E. M. M. Toscano (2001) Parametric
     and semiparametric estimations of stationary univariate ARFIMA
     model. _Brazilian Journal of Probability and Statistics_ *14*,
     185-206.

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

     'fdGPH', 'fracdiff'

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

     memory.long <- fracdiff.sim(1500, d = 0.3)
     spm <- fdSperio(memory.long$series)
     str(spm, digits=6)

