BACKGROUND Experimental results are commonly fitted by determining parameter values of suitable mathematical expressions. In case a relation exists between different data sets, the accuracy of the parameters obtained can be increased by incorporating this relationship in the fitting process instead of fitting the recordings separately. METHODS An algorithm to fit multiple measured curves simu...

This paper deals with defining measures of model closeness and establishing quantitative confidence bounds on nominal models. Confidence in a model is an indication of how uniquely identifiable the best fitting parameter values are from the data. These concepts are examined in both the linear and nonlinear regimes, with a practical example used to explore these propositions.

This study aimed to fit nonlinear regression models model the growth of characters fruit length (FL) and width (FW) pepper genotypes (Capsicum annuum L.) over time using method ordinary least squares (OLS); identify with best compare it obtained via quantile (QR) in 0.25, 0.5, 0.75 quantiles. Three (Logistic, Gompertz, von Bertalanffy) four quality evaluators were adopted: Akaike information cr...

We present a method to determine fixed points in spatiotemporal signals. The method combines a clustering algorithm and a nonlinear analysis method fitting temporal dynamics. A 144-dimensional simulated signal, similar to a Kueppers-Lortz instability, is analyzed and its fixed points are reconstructed.

We describe an end-to-end real-time S&P futures trading system. Inner-shell stochastic nonlinear dynamic models are developed, and canonical momenta indicators are derived from a fitted Lagrangian used by outer-shell trading models dependent on these indicators. Recursive and adaptive optimization using adaptive simulated annealing is used for fitting parameters shared across these shells of dy...