Sentence examples for model parameter estimations from inspiring English sources
Assuming no knowledge of the data dispersion type, we consider various count data model parameter estimations to describe this real data distribution: Poisson, negative binomial, and sCMP at various levels of m=1,2,3,4.
Model parameter estimations are given in Table S4.
An overview of the parameters, their prior distributions, the model parameter estimations and model code provides information about the model structure and the Bayesian framework (Additional file 1).
Therefore, we estimated the structure based on model parameter estimation examining which structures could reliably reproduce the experimental data with respect to the signal amplitude and duration of the signaling molecules.
Handling of missing covariate data in PopPK analyses in an appropriate way, i.e., one that does not induce bias or imprecision in model parameter estimation is important, and several methods are available to the modeler.
Cauchy Model Parameter Estimation.
Laplacian Model Parameter Estimation.
Variational Bayes techniques for model parameter estimation are used.
This practice also applies to discrete choice model parameter estimation.
(b) Mean Squared Error (MSE) versus SNR for nonlinear model parameter estimation produced by artificial signals.
The informed approach for model parameter estimation was described in a theoretical and a practical framework.
