RT_pca                package:RTisean                R Documentation

_P_C_A

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

     Performs a global SVD.

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

     RT_pca(series,l,x=0,c=1,m=c(1,2),d=1, W=0, q)

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

  series: a vector or a matrix

       l: number of data to be used 

       x: number of lines to be ignored 

       c: column to be read 

       m: no. of input columns, embedding dimension

       d: delay

       W: an integer code between 0 and 3 indicating the kind of output
          to be produced (see 'value' section)

       q: meaning depends on 'W'. 'W=2': Number of components written.
          'W=3': Projection dimensiondimensions to write the time
          series down to

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

     Depends on the 'W' option. 

       0: the vector of eigenvalues

       1: matrix of eigenvectors. The columns of the output matrix are
          the eigenvectors

       2: Transformation of the time series onto the eigenvector basis.
          The number of components printed is determined by the 'q'
          option

       3: Projection of the time series onto the first 'q' eigenvectors
          (global noise reduction)

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

     'pc'

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

     ## Not run: 
     dat<-henon(100)
     svdout<-RT_pca(dat, W=3, q=1)
     plot(svdout,t="l",xlab="Time",ylab="Projected Time series")

     ## End(Not run)

