mixgamma               package:anapuce               R Documentation

_G_a_m_m_a _m_i_x_t_u_r_e

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

     This function provides an estimation of a mixture of gamma
     distributions. The code is inspired from the varmixt package.

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

     mixgamma(VAR, dfreedom, var.init, pi.init, nmixt, stop.crit , display = TRUE, niter.max = 50000, criterion = criterion)

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

VAR         : vector of estimated variance. 

dfreedom    : degrees of freedom of the estimated variance. 

var.init    : vector of initial variances for the mixture. 

pi.init     : vector of initial prior probability for the mixture. 

nmixt       : integer: number of components in the mixture model. 

stop.crit   : the stopping relative precision limit for stopping EM
          algorithm. 

display     : boolean: should the result of model fitting be displayed
          on the screen ? 

niter.max   : integer : maximum number of iterations of the EM
          algorithm. 

criterion   : criterion for the convergence of the EM algorithm :
          either "likelihood"  for criterion base on loglikelihood
          either "parameter". 

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

     a LIST with the following components : 

BIC.crit: value of the BIC criterion

p.i     : the probability of each variance component

vars    : variances

loglike : value of the criterion base on Loglikelihood

nmixt   : number of variance components

tau     : the matrix of posterior probability that a gene belongs to
          each variance component. One row per gene, one column per
          variance component. 

VM2     : the variance attributed to each gene according to the MAP
          rule - Delmar et al. (2005) _JRSS_

VM      : the variance attributed to each gene taking into account the
          tau values - Delmar et al. (2005) _Bioinformatics_

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

     Paul Delmar and M-L Martin-Magniette

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

     'est.varmixt'

