Formal modeling approaches to cognition provide a principled characterization of observed
responses in terms of a set of postulated processes, specifically in terms of parameters that …

Estimates of road speeds have become commonplace and central to route planning, but few
systems in production provide information about the reliability of the prediction. Probabilistic …

Computational cognitive models have been used extensively to formalize cognitive
processes. Model parameters offer a simple way to quantify individual differences in how …

With small to modest sample sizes and complex models, maximum likelihood (ML)
estimation of confirmatory factor analysis (CFA) models can show serious estimation …

In this work, we explore the use of an iterative Bayesian Monte Carlo (iBMC) method for
nuclear data evaluation within a TALYS Evaluated Nuclear Data Library (TENDL) …

Motivation The feasibility of uniquely estimating parameters of dynamical systems from
observations is a widely discussed aspect of mathematical modelling. Several approaches …

Non-geniculate coralline algae (NGCA), Corallinophycidae-Rhodophyta, are characterized
by prominent calcified vegetative thalli. They exhibit broad phenotypic plasticity, and …

In this paper, we regard as a coded transmission over a frequency-selective channel. We
plan to study analytically the convergence of the turbo-detector using a maximum a …

Abstract The bivariate Stable Trait, AutoRegressive Trait, and State (STARTS) model
provides a general approach for estimating reciprocal effects between constructs over time …

Hyperbolic balance laws with uncertain (random) parameters and inputs are ubiquitous in
science and engineering. Quantification of uncertainty in predictions derived from such laws …