Time series: theory and methods
Time series: theory and methods
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
Statistical synthesis of facial expressions for the portrayal of emotion
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A comparison of multivariate autoregressive estimators
Signal Processing - Signal processing in UWB communications
Decomposition of the multi-dimensional time series identification problem
Automation and Remote Control
Evaluating exact VARMA likelihood and its gradient when data are incomplete
ACM Transactions on Mathematical Software (TOMS)
Algorithm 878: Exact VARMA likelihood and its gradient for complete and incomplete data with Matlab
ACM Transactions on Mathematical Software (TOMS)
Body sensor networks based sensor fusion for cardiovascular biosignal predictions
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
A Novel Method for Registration of US/MR of the Liver Based on the Analysis of US Dynamics
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Controlled complete ARMA independent process analysis
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Computer Based Synchronization Analysis on Sleep EEG in Insomnia
Journal of Medical Systems
Separation theorem for independent subspace analysis and its consequences
Pattern Recognition
Independent subspace analysis on innovations
ECML'05 Proceedings of the 16th European conference on Machine Learning
Detecting effective connectivity in networks of coupled neuronal oscillators
Journal of Computational Neuroscience
Personal and Ubiquitous Computing
Applied Bionics and Biomechanics - Human-Robot Interaction/Interface
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ARfit is a collection of Matlab modules for modeling and analyzing multivariate time series with autoregressive (AR) models. ARfit contains modules to given time series data, for analyzing eigen modes of a fitted model, and for simulating AR processes. ARfit estimates the parameters of AR models from given time series data with a stepwise least squares algorithm that is computationally efficient, in particular when the data are high-dimensional. ARfit modules construct approximate confidence intervals for the estimated parameters and compute statistics with which the adequacy of a fitted model can be assessed. Dynamical characteristics of the modeled time series can be examined by means of a decomposition of a fitted AR model into eigenmodes and associated oscillation periods, damping times, and excitations. The ARfit module that performs the eigendecomposition of a fitted model also constructs approximate confidence intervals for the eigenmodes and their oscillation periods and damping times.