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This model estimate is further used to guarantee nominal stability and to improve the parameter update using a line search algorithm for determining the iteration step size.
This paper presents an approach to designing the input signal for an identification experiment, in which the process model estimate is to be used to formulate and solve for a robust (in a worst case sense) optimal controller.
Our final fault model estimate is in good agreement with the M w estimates described above and is approximately consistent with the main rupture of the finite-fault model of Yarai et al. (2016) except for the strike angle and length: The strike angle was ~7° smaller and the length was ~6 km longer.
We present results both when the design is based on knowledge of the true system (in general the optimal design depends on the system itself) and for a practical two step procedure when an initial model estimate is used in the design instead of the true system.
We evaluated modeled evapotranspiration with an eddy covariance (EC) result from the established regression equation, and a scatter correlation plot for the measured and estimated transpiration indicated that the model estimate is within acceptable limits, with a correlation coefficient of R2 = 0.796.
The new measurement points are chosen to lie in those regions where the lower bound of the model estimate is lowest, while keeping a user-specified minimum distance to other measurements (similar to method 3 in [14]).
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A summary of our difference-in-difference model estimates is presented in Table 2.
A discussion on the sensitivity of the optimal input design to model estimates is provided.
The form of the probit model estimated is as follows: Neonatal=alpha NHIS+beta Socioeconomic+gamma Child+varepsilon.
Adequate test retest reliability of model estimates is a necessary precursor to examining treatment effects or longitudinal changes in individuals.
Propagation of uncertainty in parameter estimation to model estimates was assessed qualitatively.
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