findSegments           package:tilingArray           R Documentation

_F_i_t _a _p_i_e_c_e_w_i_s_e _c_o_n_s_t_a_n_t _c_u_r_v_e _t_o _a _s_e_q_u_e_n_c_e _o_f _n_u_m_b_e_r_s  -
_O_B_S_O_L_E_T_E, _p_l_e_a_s_e _u_s_e _f_u_n_c_t_i_o_n _s_e_g_m_e_n_t _i_n_s_t_e_a_d.

_D_e_s_c_r_i_p_t_i_o_n:

     This function is only here for backward compatibility - please use
     'segment'.

     The function fits a piecewise constant curve to a sequence of
     numbers using a simple least squares cost function and the dynamic
     programming algorithm described by Picard et al. (see reference).

_U_s_a_g_e:

     findSegments(x, maxcp, maxk, verbose=TRUE)

_A_r_g_u_m_e_n_t_s:

       x: Numeric (real) vector.

   maxcp: Integer (length 1): maximum number of segments (= 1 + maximum
          number of change points).

    maxk: Integer (length 1): maximum length of a segment.

 verbose: Logical: if this parameter has a positive value, various
          diagnostic output is printed.

_D_e_t_a_i_l_s:

     The complexity of the algorithm is  'length(x)*maxk' in memory and
     'length(x)*maxk*maxcp' in time.

_V_a_l_u_e:

     An object of class '"segmentation"' A list with elements 

       J: likelihood criterion

      th: matrix of segment start points

     dat: the data used for the segmentation

    call: the function call

     .

     See the vignette, and the paper cited below for details.

_N_o_t_e:

     This function is depracated and replaced by function 'segment',
     but still included for backward compability.

_A_u_t_h_o_r(_s):

     W. Huber huber@ebi.ac.uk, Joern Toedling toedling@ebi.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     A statistical approach for CGH microarray data analysis. Franck
     Picard, Stephane Robin, Marc Lavielle, Christian Vaisse, Gilles
     Celeux, Jean-Jacques Daudin, Rapport de recherche No. 5139, Mars
     2004, Institut National de Recherche en Informatique et en
     Automatique (INRIA), ISSN 0249-6399. The code of this function is
     based on the Matlab implementation presented at   <URL:
     http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil
     .html>, but it has evolved.

_E_x_a_m_p_l_e_s:

      x = rep( sin((0:4)/2*pi), each=3) + rnorm(3*5, sd=0.1)
      res = findSegments(x, maxcp=6, maxk=15)

