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Multiple emitter location and signal Parameter estimation
, 1986Processing the signals received on an array of sensors for the location of the emitter is of great enough interest to have been treated under many special case assumptions.
R. Schmidt
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On the Estimation of Contrasts in Linear Estimation
Calcutta Statistical Association Bulletin, 1973This paper examines the conditions on the coefficient matrix of the linear model under which contrasts, and contrasts alone, are estimated by contrasts.
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ESPRIT-estimation of signal parameters via rotational invariance techniques
IEEE Transactions on Acoustics Speech and Signal Processing, 1989High-resolution signal parameter estimation is a problem of significance in many signal processing applications. Such applications indude direction-of-arrival estimation, system identification, and time series analysis.
R. Roy, T. Kailath
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Journal of Mathematical Sciences, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models
, 1991This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the likelihood ratio test for cointegrating rank and finds it asymptotic distribution.
S. Johansen
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Biometrika, 1988
A time series model of the form \[ X_ t=a\cos (wt+f)+e_ t \] where \(e_ t\) is a stationary noise sequence is considered. The paper discusses a least squares procedure for estimating a, w and f of the harmonic component. One aim of the paper is to see how reliable the asymptotic theory of the estimates of w is.
John Rice, Murray Rosenblatt
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A time series model of the form \[ X_ t=a\cos (wt+f)+e_ t \] where \(e_ t\) is a stationary noise sequence is considered. The paper discusses a least squares procedure for estimating a, w and f of the harmonic component. One aim of the paper is to see how reliable the asymptotic theory of the estimates of w is.
John Rice, Murray Rosenblatt
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A-posteriori estimation of the error in the error estimate
Computer Methods in Applied Mechanics and Engineering, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
D.K. Datta +4 more
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Structural Model Evaluation and Modification: An Interval Estimation Approach.
Multivariate Behavioral Research, 1990Dans les differentes procedures existantes pour l'evaluation et les modifications sequentielles des modeles structuraux, l'auteur s'attache a discuter celle connue sous le terme PMM.
J. H. Steiger
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Novel approach to nonlinear/non-Gaussian Bayesian state estimation
, 1993An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters. The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm.
N. Gordon +2 more
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2007
This chapter describes the four main methods of estimating and their approximate levels of accuracy. These methods are: subjective (±20%–40%), parametric (±10%–20%), comparative (±10%) and analytical (±5%). The need to always allow a contingency is stressed and a diagram shows how the accuracy percentage improves as the project moves from the concept ...
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This chapter describes the four main methods of estimating and their approximate levels of accuracy. These methods are: subjective (±20%–40%), parametric (±10%–20%), comparative (±10%) and analytical (±5%). The need to always allow a contingency is stressed and a diagram shows how the accuracy percentage improves as the project moves from the concept ...
openaire +3 more sources