We use a simple algorithm that captures time-dependent preference development, with which we can study the dynamics of a learning process in a rich environment (as in van der Post and Hogeweg 2006).
We first modeled the maturation of these constructs in-vitro to capture time-dependent changes.
In addition to the signaling activation data at each time point, our PLS-DA models incorporated several data-derived signaling metrics to capture time-dependent features encoded in the signaling time courses31,33.
Results generated by applying the developed algorithms for anisotropic, strain-controlled tensile (with comparison to typical experimental data) and constant-stress creep tests are presented to demonstrate the ability of the present models to accurately capture time-dependent anisotropic material behavior.
We generated simulated data to show the efficacy of eLSA in capturing time-dependent association patterns, such as time-delayed associations and associations within a subinterval.
We find that, after controlling for observed factors like employment and health status, and after specifying a dynamic model that attempts to capture time-dependent unobserved effects, individuals who have multiple transitions into and out of Medicaid have higher emergency room utilization, more office visits, more hospitalizations, and refill their prescriptions less often.
The simulation results show that the simple capacitance model satisfactorily captures the long time dependent behavior between injectors and producers.
A dynamic mathematical model such as ours captures these complex time dependent trends in tuberculosis better than linear extrapolation techniques typically used to estimate the impact of smoking.
This model captures the time-dependent characteristics of the bearing contact due to the orbital motion of the rolling elements.
Using the microbial community and gene expression datasets, we demonstrated that eLSA uniquely captures additional time-dependent associations, including local and time-delayed association patterns, when compared to ordinary correlation methods, such as PCC.
CGPM applied to the Cox model with a time dependent treatment effect provides an R D t) estimate not yet capturing the initial harmful treatment effect.
