INSPIRE

Chebyshev approximation and composition of functions in matrix product states for quantum-inspired numerical analysis

This work explores the representation of univariate and multivariate functions as matrix product states (MPS), also known as quantized tensor-trains (QTT). It proposes an algorithm that employs ...
Frontiers

Monte Carlo Simulations for the Analysis of Non-linear Parameter Confidence Intervals in Optimal Experimental Design

Especially in biomanufacturing, methods to design optimal experiments are a valuable technique to fully exploit the potential of the emerging technical possibilities that are driving experimental ...
Scientific Research Publishing

Linear Dimension Reduction for Multiple Heteroscedastic Multivariate Normal Populations ()

1 Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AK, USA. 2 Department of Statistical Science, Baylor University, Waco, TX, USA. The fact that the Bayes ...
Scientific Research Publishing

J. Nyblom, “Invariant Tests for Covariance Structures in Multivariate Linear Model,” Journal of Multivariate Ana- lysis, Vol. 76, 2001, pp. 294-315. doi:10.1006/jmva.2000.1918

ABSTRACT: Certain locally optimal tests for deterministic components in vector time series have associated sampling distributions determined by a linear combination of Beta variates. Such ...
IEEE

Optimal triangular approximation for linear stable multivariable systems

Abstract: This paper deals with the problem of obtaining a stable triangular approximation for a linear, square, stable, discrete-time MIMO system. We solve this problem through an analytic procedure ...
IEEE

Stochastic approximation algorithm for the identification of linear multivariable systems

Abstract: A stochastic approximation algorithm is presented for on-line identification of linear, multivariable, discrete-time systems from noisy data without prior knowledge of the statistics of ...