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Many applications of block designs exhibit neighbor and edge ef-fects. A popular remedy is to use the circular design coupled with the interference model. The search for optimal or efficient designs h...
Identication of a spatial Durbin model is a concern in the spatial econometrics literature. The concern is similar to the identication of the endogenous e¤ect, the contextual e¤ect and correlation e...
Motivated by applications in high-dimensional data analysis where strong signals often stand out easily and weak ones may be indistinguishable from the noise, we develop a statistical framework to pro...
Recently, an extension of independent component analysis (ICA) from one to multiple datasets, termed independent vector analysis (IVA), has been the subject of significant research interest. IVA has a...
The classical approach to linear system identification is given by parametric Prediction Error Methods (PEM). In this context, model complexity is often unknown so that a model order selection step is...
We introduce GP-FNARX: a new model for nonlinear system identification based on a nonlinear autoregressive exogenous model (NARX) with filtered regressors (F) where the nonlinear regression problem is...

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