squeezeMVar               package:betr               R Documentation

_S_m_o_o_t_h _s_a_m_p_l_e _c_o_v_a_r_i_a_n_c_e _m_a_t_r_i_c_e_s

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

     An internal function to smooth a set of sample covariance matrices
     by computing empirical Bayes posterior means.

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

     squeezeMVar(S, df, Lambda = NULL, nu = NULL)

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

       S: a list of covariance matrices

      df: numeric vector of degrees of freedom for covariance matrices

  Lambda: use this target covariance matrix instead of calculating it
          from the data

      nu: use this nu instead of calculating it from the data

_D_e_t_a_i_l_s:

     Calculate shrinkage estimates for covariance matrices using the
     procedure of Tai and Speed (2006) and Smyth (2004)

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

varPost : list of posterior covariance matrices

varPrior : target covariance matrix

dfPrior : prior degrees of freedom

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

     Martin Aryee

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

     Smyth, G. Linear models and empirical bayes methods for assessing
     differential expression in microarray experiments. Statistical
     applications in genetics and molecular biology (2004) vol. 3

     Tai, Y and Speed, T. A multivariate empirical Bayes statistic for
     replicated microarray time course data. Annals of Statistics
     (2006) vol. 34 (5) pp. 2387-2412

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

     'betr'

