Sentence examples for model parameters very from inspiring English sources
They were designed in such a way that with a unique set of model parameters, very different internal states can be addressed throughout cyclic loadings.
WinBUGS has become popular even among frequentist statisticians because, when sample sizes are large and the assumed distributions on unknown model parameters are very broad (i.e., noninformative or "flat" priors), Bayesian inference will provide results very close to those obtained through a frequentist approach (Carlin and Louis 2000).
The results show that this method can estimate model parameters from very short record lengths.
From the fourth inversion result, which was obtained within 5 min, VR improved to 96%, and all model parameters became very stable.
The signals were sampled with 2.1 kHz, that allows to derive all dual-satellite model parameters for very slow variations (state parameters) and slow- and fast variations (Loo parameters).
They showed that the occurrence of the heavy shadow (corresponding to NLOS severe in our work) state and the channel model parameters are very different in dense urban areas.
However, as shown in Fig. 2, the confidence interval for the model parameters was very similar for the three conditions.
Sensitivity analysis of model parameters is very important to design and control strategies as well as being a direction to future research.
This paper will discuss a clustering methodology using a surrogate heat transfer algorithm that allows propagation of the uncertainties in the model parameters using a very limited series of full simulations.
The combined application of the online framework and the joint estimation of sensitive model parameters provides a very efficient usage of measurement data reducing the overall number of experiments.
Moreover, it is shown that the elliptical approximation of confidence regions of nonlinear model parameters can be very poor sometimes and that more accurate likelihood confidence regions can be constructed with PSO, allowing for more reliable statistical analysis of the significance of parameter estimates.
