sbgcop.package

sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a G

sbgcop-package            package:sbgcop            R Documentation

_S_e_m_i_p_a_r_a_m_e_t_r_i_c _B_a_y_e_s_i_a_n _G_a_u_s_s_i_a_n _c_o_p_u_l_a _e_s_t_i_m_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This package estimates parameters of a Gaussian copula, treating
     the univariate marginal distributions as nuisance parameters as
     described in Hoff(2007). It also provides a semiparametric
     imputation procedure for missing multivariate data.

_D_e_t_a_i_l_s:


       Package:  sbgcop
       Type:     Package
       Version:  0.95
       Date:     2007-03-09
       License:  GPL Version 2 or later

     This function produces MCMC samples from the posterior
     distribution of a correlation matrix, using a scaled
     inverse-Wishart prior distribution and an extended rank 
     likelihood. It also provides imputation for missing values in a
     multivariate dataset.

_A_u_t_h_o_r(_s):

     Peter Hoff <[e-mail]>

_R_e_f_e_r_e_n_c_e_s:

     Hoff (2007) ``Extending the rank likelihood for semiparametric
     copula estimation''

_E_x_a_m_p_l_e_s:

     fit<-sbgcop.mcmc(swiss)
     summary(fit)
     plot(fit)