In order to estimate the model parameters we follow the guidelines given by the CSEP laboratory.
As for the magnetic model parameters we have: qi,k+1 = q i,k + δq i.
For interval estimation of the model parameters, we require the 4×4 total observed information matrix J.
For interval estimation on the model parameters, we can evaluate the estimated observed information matrix (J widehat {boldsymbol {theta }})) numerically.
For obtaining interval estimation and hypothesis testing on the model parameters, we need the observed information matrix.
To estimate the model parameters, we use real-world data on the 2013 midterm elections in Argentina.
By adjusting model parameters, we manipulated the 'intention' of VP as cooperative or competitive with the human's instructed goal.
In order to efficiently estimate the model parameters, we derive two scalable co-clustering algorithms based on variational inference.
To effectively learn the model parameters, we automatically collect large-scale mention-entity pairs from Wikipedia as training data.
Furthermore, the inversion in the logarithmic space of the model parameters forces and guarantees the positivity of the model parameters we seek.
After estimating the propagation model parameters, we carried out two experiments, both based on a localization application: (1) a practical experiment; and (2) a simulation experiment.
