runHomHMM              package:snapCGH              R Documentation

_A _f_u_n_c_t_i_o_n _t_o _f_i_t _u_n_s_u_p_e_r_v_i_s_e_d _H_i_d_d_e_n _M_a_r_k_o_v _m_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     This function fits an unsupervised Hidden Markov model to a given
     'MAList or \code{SegList}'

_U_s_a_g_e:

     runHomHMM(input, vr = 0.01,
                     maxiter = 100, criteria = "AIC", delta = NA,
                     full.output = FALSE, eps = 0.01)

_A_r_g_u_m_e_n_t_s:

   input: an object of class 'MAList' or 'SegList'

      vr: Gets passed to the function 'hidden' as the 'pshape'
          arguement.

 maxiter: Gets passed to the function 'hidden' as the 'iterlim'
          arguement. 

criteria: Choice of which selection criteria should be used in the
          algorithm.  The choices are either AIC or BIC

   delta: Delta value used of the BIC is selected.  If no value is
          entered it defaults to 1.

full.output: if true the SegList output includes a probability that a
          clone is in its assigned state and a smoothed value for the
          clone.

     eps: parameter controlling the convergence of the EM algorithm. 

_S_e_e _A_l_s_o:

     'runDNAcopy' 'runGLAD' 'SegList'

