Likelihood-based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: A simulation study

Accelerating simulations of computationally intensive first principle models using accurate quasi-linear parameter varying models

Likelihood based hyphothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study

Robust estimation of the noise variance from background MR data progress in biomedical optics and imaging

Estimating time-series models from irregularly spaced data

Time-series analysis if data are randomly missing

Estimation of the noise variance from the background histogram mode of an Magnetic Resonance Image

Monitoring of industrial processing using large scale first principles models

Accelerating simulations of first principle models of complex industrial systems using qusi linear parameter varying models

Design of a kalman filter when no noise covariance information is available

A Likelihood Ratio Test for Functional MRI Data Analysis to Account for Colored Noise

Estimating time series models from irregularly sampled data

On model selection for state estimation for nonlinear systems

Order selection for autoregressive spectral estimation with randomly mising data

Accelerating large-scale non-linear models for monitoring and control using spatial and temporal correlations

Autoregressive spectral analysis when observations are missing

Autoregressive order selection in missing data problems

Estimation of time series spectra with randomly missing data

Autoregressive spectral analysis with randomly missing data

Application of autoregressive spectral analysis to missing data problems