surrogates              package:RTisean              R Documentation

_M_a_k_i_n_g _s_u_r_r_o_g_a_t_e _d_a_t_a

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

     Reads data from a file and creates surrogate data with the same
     Fourier amplitudes and the same distribution of values.

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

     surrogates(series, n = 1, i, S = FALSE, I, l, x = 0, m, c)

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

  series: a vector or a matrix.

       n: number of surrogates.

       i: number of iterations. 

       S: make spectrum exact rather than distribution. 

       I: seed for random numbers. 

       l: number of points. 

       x: number of values to be skipped. 

       m: number of columns to be read.

       c: columns to be read. 

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

     If 'c' is chosen larger than 1, multivariate surrogates are
     prepared. In that case, also the relative Fourier phases of the
     channels are matched to those of the data. Since for finite
     length, distribution and spectral properties  cannot be guaranteed
     exactly at the same time, the default output contains the 
     iteration stage with the exact amplitudes. With the parameter 'S'
     set, the stage with  the exact spectrum (resp. relative phases) is
     given. Asymptotically, the difference between both should converge
     to zero.  It is advisable to select a suitable sub-sequence to
     minimize end effects by  using 'endtoend' before preparing
     surrogates

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

     A vector or a matrix containing the surrogate data as columns.

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

     T. Schreiber and A. Schmitz, Improved surrogate data for
     nonlinearity  tests, Phys. Rev. Lett. 77, 635 (1996).

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

     'endtoend'

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

     ## Not run: 
     dat <- logistic(1000)
     surr <- surrogates(dat)
     Z <- cbind(dat,surr)[1:100,]
     colnames(Z) <- c("data","surrogate")
     plot.ts(Z,  mar.multi = c(0, 5.1, 1, 2.1 ),main="Logistic model time series")
     ## End(Not run)

