lfo.test               package:RTisean               R Documentation

_L_o_c_a_l _l_i_n_e_a_r _a_n_s_a_t_z

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

     Estimates the average one step prediction error of for a local
     linear ansatz fit.

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

     lfo.test(series, l, x = 0, c=1, m = c(1,2), d = 1, n, k = 30, r, f = 1.2, s = 1, C)

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

  series: a vector or a matrix. 

       l: number of data to use. 

       x: number of lines to be ignored. 

       c: column to be read. 

       m: embedding dimension. 

       d: delay for the embedding. 

       n: number of points for which the error should be calculated.

       k: minimal numbers of neighbors for the fit. 

       r: neighborhood size to start with. 

       f: factor to increase the neighborhood size if not enough
          neighbors were found. 

       s: steps to be forecasted. 

       C: width of causality window.

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

     A scalar corresponding to the relative forecast error, namely the
     forecast error  devided by the standard deviation of the data.

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

     ## Not run: 

     library(tseriesChaos)
     dat <- rossler.ts
     errors <- NULL
     for(i in 1:100)
             errors[i] <- lfo.test(dat,s=i)

     plot(errors,t="l",xlab="Forecasted steps", ylab="Relative error",main="Relative forecast error for a local linear fit")  

     ## End(Not run)

