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A SIMPLE ESTIMATOR OF COINTEGRATING VECTORS IN HIGHER ORDER INTEGRATED SYSTEMS
Efficient estimators of cointegrating vectors are presented for systems involving deterministic components and variables of differing, higher orders of integration. The estimators are computed usingExpand
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The statistical theory of linear systems
Publisher Summary The chapter discusses the development of a rather complete inferential theory for ARMAX models. The first problem in the development is the coordinatization of spaces of suchExpand
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Nonnegative realization of a linear system with nonnegative impulse response
Let H(z) be a rational transfer function, with associated nonnegative impulse response sequence. The paper considers the question: When does there exist a triple A/spl isin/R/sup N/spl times/N/,Expand
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Statistical analysis of novel subspace identification methods
TLDR
In this paper four subspace algorithms which are based on an initial estimate of the state are considered. Expand
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Identifiability in dynamic errors-in-variables models
This paper is concerned with the identifiability of scalar linear dynamic errors-in-variables systems. The analysis is based on second moments only. The set of feasible systems corresponding to givenExpand
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Time series econometrics
TLDR
Major lines of the development of time series econometrics are discussed. Expand
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A Structure Theory for Linear Dynamic Errors-in-Variables Models
We deal with problems connected with the identification of linear dynamic systems in situations when inputs and outputs may be contaminated by noise. The case of uncorrelated noise components and theExpand
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MULTIVARIATE AR SYSTEMS AND MIXED FREQUENCY DATA: G-IDENTIFIABILITY AND ESTIMATION
This paper is concerned with the problem of identifiability of the parameters of a high frequency multivariate autoregressive model from mixed frequency time series data. We demonstrateExpand
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Consistency and relative efficiency of subspace methods
TLDR
We give a consistency proof for two subspace methods and a simulation study comparing them to the maximum-likelihood method. Expand
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