likelihoods-methods         package:Rtreemix         R Documentation

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

     This function predicts the (log, weighted) likelihoods of the
     samples in a given dataset according to a given mutagenetic trees
     mixture model. The dataset and the model have to be specified.

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

     ## S4 method for signature 'RtreemixModel, RtreemixData':
     likelihoods(model, data)

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

   model: An 'RtreemixModel' object specifying the probabilistic
          framework in which the likelihoods of the genetic patterns
          are computed.

    data: An 'RtreemixData' object giving the samples for which the
          likelihoods are to be calculated.

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

     This method returns an 'RtreemixStats' object that containes the
     weghted- and log-likelihoods of the samples in the given dataset
     with respect to the given mutagenetic trees mixture model.

_A_u_t_h_o_r(_s):

     Jasmina Bogojeska

_R_e_f_e_r_e_n_c_e_s:

     Learning multiple evolutionary pathways from cross-sectional data,
     N. Beerenwinkel et al.

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

     'RtreemixData-class', 'RtreemixModel-class', 'fit-methods',
     'distribution-methods'

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

     ## Create an RtreemixData object from a randomly generated RtreemixModel object.
     rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
     data <- sim(model = rand.mod, no.draws = 300)
     show(data)

     ## Compute the likelihoods of the samples in data with respect to the model rand.mod
     mod.stat <- likelihoods(model = rand.mod, data = data)
     show(mod.stat)

