Possibly, these results pertain mostly to parameter variation that results from matching a networked system with many species to selected time-series data for only few species, which may behave differently from general optimization.
Instead of using kinetic information, one could also select some of the decoupled equations and use optimization methods to fit the selected model to the time series data (e.g.[ 24, 25]).
To understand the general water quality situation, the time series data of selected water quality parameters were analyzed in an urban river in Peninsular Malaysia.
The behavior test shows simulated behavior compared to available time series data of selected variables, demand, and number of ophthalmologists employed (refer to Additional file 1).
Instead of using an automatic procedure for the selection of magnetosheath events, we closely investigate each of the magnetic field time series data to select the 10-min magnetosheath intervals out of 101 magnetosheath crossings.
The basic idea is to fit various models to time series data, and select one of those models using Bayesian model comparison.
With time series data, the time lag should be carefully selected based on users understanding of the dataset, in order to reveal the information embedded in time lags.
The remaining four input vectors are selected using the most common approach in which selection of the input vector comprising of the sequential time series data.
The proposed algorithm provides superior performance for the selected datasets than the robust and widely used ARIMA methodology in predicting time series data.
We have given an overview of model comparison methods suitable for selecting a plausible network motif structure among a set of candidate models for time series data on gene regulation.
The selected model was validated regarding the robustness of the inferred network against small changes in the time series data, reflecting measurement error due to technical or biological variance.
