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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...
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...
The paper discusses two methods of optimal excitation signal design for identification with Maximum Likelihood parameter estimation: The ‘classical’, dispersion function based method, and a new, semid...
We consider the problem of estimating a pattern of faults, represented as a binary vector, from a set of measurements. The measurements can be noise corrupted real values, or quantized versions of noi...
Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expressi...
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inputs and outputs are ...
Sharing criminal history record information: the Interstate Identification Index.
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...
Bayesian approaches to optimization under bandit feedback have recently become quite popular in the machine learning community. Methods of this type have been found to have not only very good empirica...
In this paper we studied about the wavelet identification of the thresholds and time delay for more general case without the constraint that the time delay is smaller than the order of the model. Here...
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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