Some estimators may be used to implement the estimation algorithms.
This package implemented the estimation method of GAM described in section 2.4.
Based on (10), we can implement the estimation of velocity and crossing point.
Precisely, MAMPC spends 7.1s to implement the estimation, whereas AMPC and FAMPC need 1400.5 and 105.8 s, respectively.
Meanwhile, to implement the estimation of shear wave from well logs, a corresponding log interpretation method for gas-bearing shale is also studied.
The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.
We design and implement the estimation process and verify it by experiments, which shows that our method efficiently reduces those artifacts.
A straightforward way would be to implement the estimation algorithm completely with a particle filter, which is the most general method with respect to system nonlinearities, but depending on the considered number of paths the state space in such a filter becomes large, and it becomes difficult to cover the entire space with a reasonable number of particles.
To implement the estimation, assume that the first order conditions are not exactly fulfilled, but hold subject to a non-systematic error that may stem from several sources, such as optimization errors, and the differences between anticipated and realized output price or the wage rate per unit of quality.
Thus we can be able to implement the estimation of adoption rate and its determinants from the exposed sub sample alone, if the conditional independence assumption holds and if potential adoption is independent of vectors of exposure determinants conditional on the vector of adoption determinants.
