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    -------- spatial error model estimation functions --------

    compare_models    : An example of using sar_g() sem_g() Gibbs sampling
    compare_models2   : An example of using sar_g() sem_g() Gibbs sampling
    compare_weights   : An example of using sem_c() function
    compare_weights2  : An example of using sem_c() function
    f2_sem            : evaluates SEM log-likelihood -- given ML parameters using sparse matrix algorithms
    f_sem             : evaluates SEM concentrated log-likelihood using sparse matrix algorithms
    prt_bmae          : print results from sar_gcbma, sem_gcbma functions
    prt_sem           : Prints output using spatial error model results structures
    sem               : computes spatial error model estimates
    sem_c             : Bayesian log-marginal posterior for the spatial error model
    sem_d             : An example of using sem
    sem_d2            : An example of using sem() on a large data set
    sem_d3            : An example of using sem() on a large data set
    sem_g             : Bayesian estimates of the spatial error model
    sem_gcbma         : MC^3 x-matrix specification for homoscedastic SEM model
    sem_gcbmad        : compute posterior probabilities of
    sem_gd            : An example of using sem_g()
    sem_gd2           : An example of using sem_g()
    sem_testd         : A timing comparison of heteroscedastic versus homoscedastic on small and large datasets
    semp_g            : Bayesian estimates of the spatial probit error model
    semp_gd           : An example of using sempp_g() Gibbs sampling spatial autoregressive probit model
    semp_gd2          : An example of using semp_g()
    test_bayes        : A comparison of Bayesian and ML estimates
    test_bayes2       : A comparison of Bayesian and ML estimates
    test_bayes3       : A comparison of Bayesian and ML estimates
    test_bayes4       : A comparison of Bayesian and ML estimates
    test_bayes5       : A comparison of Bayesian and ML estimates
    test_maxlik       : A test of the accuracy of max-like estimates