Estimate distribution parameters by GMM based on matching quantiles
Currently mainly to try out different requirements for GMM when we cannot calculate the optimal weighting matrix.
Methods
| calc_cov_params(moms, gradmoms[, weights, ...]) | calculate covariance of parameter estimates |
| calc_weightmatrix(moms[, method, wargs]) | calculate omega or the weighting matrix |
| cov_params(**kwds) | |
| fit([start]) | Estimate the parameters using default settings. |
| fitgmm(start[, weights]) | estimate parameters using GMM |
| fititer(start[, maxiter, start_weights, ...]) | iterative estimation with updating of optimal weighting matrix |
| fitonce([start, weights, has_optimal_weights]) | fit without estimating an optimal weighting matrix and return results |
| fitstart() | |
| get_bse([method]) | method option not defined yet |
| gmmobjective(params, weights) | objective function for GMM minimization |
| gradient_momcond(params[, epsilon, method]) | |
| jtest() | overidentification test |
| momcond(params) | moment conditions for estimating distribution parameters by matching |
| momcond_mean(params) | mean of moment conditions, |
Attributes
| bse | standard error of the parameter estimates |