[Return to Master Index]

    -------- spatial Durbin model estimation functions --------

    compare_models  : An example of using sdm_g() sem_g() Gibbs sampling
    f2_sdm          : evaluates llike for the spatial durbin model
    f_sdm           : evaluates concentrated log-likelihood for the
    model_compare2  : An example of using sdm_g() Gibbs sampling
    model_probs     : computes and prints posterior model probabilities using log-marginals
    plt_sdm         : Plots output using SDM model results structures
    prt_sdm         : Prints output using sdm results structures
    sdm             : computes spatial durbin model estimates
    sdm_d           : An example of using sdm() max likelihood
    sdm_d2          : An example of using sdm() on a large data set
    sdm_g           : Bayesian estimates of the heteroscedastic spatial durbin model
    sdm_gd          : An example of using sdm_g() Gibbs sampling
    sdm_gd2         : An example of using sdm_g() on a large data set
    sdmp_g          : Bayesian estimates of the heteroscedastic spatial durbin probit model
    sdmp_gd         : An example of using sdmp_g() Gibbs sampling
    sdmp_gd2        : An example of using sdmp_g() on a large data set
    sdmt_g          : Bayesian estimates of the heteroscedastic spatial durbin tobit model
    sdmt_gd         : An example of using sdmt_g() Gibbs sampling
    sdmt_gd2        : An example of using sdmt_g() on a large data set