Multivariate prediction and matrix Szegő theory
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Publication:1950170
DOI10.1214/12-PS200zbMath1285.60038arXiv1203.0962MaRDI QIDQ1950170
Publication date: 10 May 2013
Published in: Probability Surveys (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1203.0962
multivariate predictionSzegő's theoremvector-valued stationary processmultivariate orthogonal polynomials on the unit circleVerblunsky's theorem
Stationary stochastic processes (60G10) Toeplitz operators, Hankel operators, Wiener-Hopf operators (47B35) Prediction theory (aspects of stochastic processes) (60G25)
Related Items (11)
Coefficient stripping in the matricial Nehari problem ⋮ The Life, Work, and Legacy of P. L. Chebyshev ⋮ Prediction theory for stationary functional time series ⋮ Szegő's theorem and its probabilistic descendants ⋮ Sum rules and large deviations for spectral measures on the unit circle ⋮ Modelling and Prediction of Financial Time Series ⋮ The two-periodic Aztec diamond and matrix valued orthogonal polynomials ⋮ CMV matrices, a matrix version of Baxter's theorem, scattering and de Branges spaces ⋮ Closed-form expression for finite predictor coefficients of multivariate ARMA processes ⋮ Hardy, Littlewood and probability ⋮ Aspects of prediction
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