Modelling non-stationary ‘Big Data’

Non - Stationary Bayesian Modelling and

Modelling Non-Linear and Non-Stationary Time Series

Data Computational Modelling of Multivariable Non-Stationary Noisy Linear Systems by MOESP_AOKI_VAR Algorithm

The main objective of this work is to develop a recursive algorithm for identification in the state-space of linear stochastic discrete multivariable non-stationary system; a computational process called MOESP_AOKI_VAR is proposed and implemented to achieve this. The proposed algorithm is based on the subspace methods: Multivariable Output-Error State Space (MOESP), used for computational model...

Wave data assimilation using non-stationary kriging

We present a fast sequential assimilation technique for conditioning wave simulations using buoy data. It is based on non-stationary kriging that uses a separable space-time variogram. This variogram is estimated from the history of simulations, as a collection of maps of variances of increments between the logarithms of simulated and observed wave heights. The method finally provides a set of ...

Data alignment with non-stationary shaping filters

Cross-correlation provides a method of calculating a static shift between two datasets. By cross-correlating patches of data, I can calculate a “warp function” that dynamically aligns the two datasets. By exploiting the link between cross-correlation and shaping filters, I calculate warp functions in a more general way, leveraging the full machinery of geophysical estimation. I compare warp fun...