segment             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: _s_e_g_m_e_n_t_a_t_i_o_n _b_y _d_y_n_a_m_i_c
_p_r_o_g_r_a_m_m_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     The function fits a piecewise constant curve to one or multiple
     sequences of measurements, using a least squares cost function and
     an O(n) dynamic programming algorithm (see references).

_U_s_a_g_e:

     segment(y, maxseg, maxk)

_A_r_g_u_m_e_n_t_s:

       y: Numeric matrix. Rows correspond to the 'x'-variable, columns
          to replicate measurements at the same value of 'x'.
          Breakpoints are fitted along the 'x'-axis. For example, the
          'x'-variable can be genomic coordinates or time. The
          segmentation will be along the rows of 'y'.

  maxseg: integer of length 1, maximum number of segments (= 1 +
          maximum number of change points).

    maxk: integer of length 1, maximum length of a single segment.

_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_u_t_h_o_r(_s):

     W. Huber huber@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 = segment(x, maxseg=6, maxk=15)

