BLP_data                Prepares data and parameters related to the BLP
                        algorithm for estimation.
demographicData_cereal
                        Draws for observed heterogeneity in Nevo's
                        cereal example.
dstddelta_wrap          Calculates derivatives of all shares with
                        respect to all mean utilities in a given
                        market.
dstdtheta_wrap          Calculates derivatives of all shares with
                        respect to all non-linear parameters in a given
                        market.
dummies_cars            Ownership matrix in BLP's car example.
estimateBLP             Performs a BLP demand estimation.
getDelta_wrap           Performs a contration mapping for a given set
                        of non-linear parameters.
getJacobian_wrap        Calculating the Jacobian for a given set of
                        non-linear parameters and mean utilities.
getShareInfo            Calculates information related to predicted
                        shares for a given set of non-linear parameters
                        and data.
get_elasticities        Calculates elasticities for a given variable
                        and market.
gmm_obj_wrap            Calculating the GMM objective for a given set
                        of non-linear parameters.
originalDraws_cereal    Draws for unobserved heterogeneity in Nevo's
                        cereal example.
productData_cars        Product data of BLP's car example.
productData_cereal      Product data of Nevo's cereal example.
simulate_BLP_dataset    This function creates a simulated BLP dataset.
theta_guesses_cereal    Parameter starting guesses for Nevo's cereal
                        example.
update_BLP_data         Updates the set of linear, exogenous, random
                        coefficient, share or mean utility variable in
                        the data object.
w_guesses_cereal        Mean utility starting guesses for Nevo's cereal
                        example.
