Acceptable values of Rhat ranged from 1.0 to 1.2; this is essentially a ratio of the calibrated model parameter variance between the four Markov chains to the variance within a chain.
Ceteris paribus, this will counter the aforementioned inflation of model-parameter variances [39, ch. 5.4].
Ceteris paribus, this will counter the aforementioned inflation of model-parameter variances [ 39, ch. 5.4].
Control G. RIC model Parameter vector Variance of, Shape factor of, Nonlinear RC model Parameter vector Variance of, Shape factor of, Cramer-Rao Lower Bound (CRLB) [11] is defined as (18).
A global variance-based method (Sobol 2001) is applied here, that considers the total output variance and determines the contribution of each model parameter to this variance by itself and through interactions with other parameters.
In order to account for the effect of uncertainty in the model parameters, mean-variance robust optimization is performed, allowing a trade-off between performance and robustness.
Under the assumption of normality of the error term, the mean on the untransformed scale can be directly estimated from the estimates of model parameters and variance.
The likelihood for L copies of the original data is denoted by { L(α ; C )} L. It was shown by Lele et al. [ 24, 25] that when L is large enough, π L (α | C (L )) will converge to a multivariate Normal distribution with the mean given by the MLE of the model parameters and variance-covariance matrix equal to 1/ L times the inverse of the Fisher information matrix for the MLE.
Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach.
Here we compare this method to the nonlinear Sigma-Point approach for a nonlinear, multi-stable model and show its advantage for model discrimination, especially for large parameter variances.
The actual model parameters and stratum variances were estimated separately for each survey.
