old_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  """Usage example.
  
  """
  from __future__ import print_function, division
  
  import numpy as np
  
  from argamma import ARG, ARGparams, ARGGMM
  
  __author__ = "Stanislav Khrapov"
  __email__ = "khrapovs@gmail.com"
  __status__ = "Development"
  
  
  def play_with_arg():
      param = ARGparams()
      print(param)
  
      argmodel = ARG()
      uarg = np.linspace(-50, 100, 100)
      argmodel.plot_abc(uarg)
  
      argmodel.plot_vsim()
  
      vol = argmodel.vsim_last(nsim=10)
      print(vol.shape)
  
      argmodel.plot_vlast_density(nsim=1000)
  
  def estimate_mle():
      """Try MLE estimator."""
      param_true = ARGparams()
      argmodel = ARG(param=param_true)
      nsim, nobs = 1, 500
      vol = argmodel.vsim(nsim=nsim, nobs=nobs).flatten()
      argmodel.load_data(vol=vol)
      param_final, results = argmodel.estimate_mle(param_start=param_true)
  
      print('True parameter:', param_true)
      print('Final parameter: ', param_final)
      print(type(results))
  
  def estimate_gmm():
      """Try GMM estimator."""
      param_true = ARGparams()
      argmodel = ARGGMM(param=param_true)
      nsim, nobs = 1, 500
      vol = argmodel.vsim(nsim=nsim, nobs=nobs).flatten()
      argmodel.load_data(vol=vol)
      uarg = np.linspace(.1, 10, 3) * 1j
      results = argmodel.gmmest(param_true.theta, uarg=uarg, zlag=2)
  
      print('True parameter:', param_true)
      print('Final parameter: ', ARGparams(theta=results.theta))
      print('Std: ', results.tstat)
      results.print_results()
  
  
  if __name__ == '__main__':
      #play_with_arg()
      #estimate_mle()
      estimate_gmm()
  
new_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  """Usage example.
  
  """
  from __future__ import print_function, division
  
  import numpy as np
  
  from argamma import ARG, ARGparams
  
  __author__ = "Stanislav Khrapov"
  __email__ = "khrapovs@gmail.com"
  __status__ = "Development"
  
  
  def play_with_arg():
      param = ARGparams()
      print(param)
  
      argmodel = ARG()
      uarg = np.linspace(-50, 100, 100)
      argmodel.plot_abc(uarg)
  
      argmodel.plot_vsim()
  
      vol = argmodel.vsim_last(nsim=10)
      print(vol.shape)
  
      argmodel.plot_vlast_density(nsim=1000)
  
  def estimate_mle():
      """Try MLE estimator."""
      param_true = ARGparams()
      argmodel = ARG(param=param_true)
      nsim, nobs = 1, 500
      vol = argmodel.vsim(nsim=nsim, nobs=nobs).flatten()
      argmodel.load_data(vol=vol)
      param_final, results = argmodel.estimate_mle(param_start=param_true)
  
      print('True parameter:', param_true)
      print('Final parameter: ', param_final)
      print(type(results))
  
  def estimate_gmm():
      """Try GMM estimator."""
      param_true = ARGparams()
      argmodel = ARGGMM(param=param_true)
      nsim, nobs = 1, 500
      vol = argmodel.vsim(nsim=nsim, nobs=nobs).flatten()
      argmodel.load_data(vol=vol)
      uarg = np.linspace(.1, 10, 3) * 1j
      results = argmodel.gmmest(param_true.theta, uarg=uarg, zlag=2)
  
      print('True parameter:', param_true)
      print('Final parameter: ', ARGparams(theta=results.theta))
      print('Std: ', results.tstat)
      results.print_results()
  
  
  if __name__ == '__main__':
      #play_with_arg()
      #estimate_mle()
      estimate_gmm()
  
subject: Resolve conflict