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Generalized two-stage Kalman estimator
Proceedings of the 36th IEEE Conference on Decision and Control, 2002This paper presents an optimal two-stage estimator for discrete-time stochastic systems subject to disturbances evolving in accordance with a dynamic state equation. The proposed two-stage estimator gives an optimum state estimate expressed as x/sub k/k//sup 1/=x/sub k/k//sup 1/+/spl beta//sub k/k/ x/sub k/k//sup 2/, where x/sub k/k//sup 1/ and x/sub k/
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Robust Two‐Stage Estimation in Hierarchical Nonlinear Models
Biometrics, 2001Summary. Hierarchical models encompass two sources of variation, namely within and among individuals in the population; thus, it is important to identify outliers that may arise at each sampling level. A two‐stage approach to analyzing nonlinear repeated measurements naturally allows parametric modeling of the respective variance structure for the ...
B Y, Yeap, M, Davidian
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The Nonlinear Two-Stage Least-Squares Estimator
Journal of Econometrics, 1974In this paper we consider estimation of the parameters of a single equation of a simultaneous equations model which is nonlinear both in variables and paarmeters. Such a model has never been analyzed in the literature to the best of our knowledge. Models in which the nonlinearity appears only in variables or only in parameters have been previously ...
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TSGYE: Two-Stage Grape Yield Estimation
2020Vision-based grape yield estimation provides a cost-effective solution for intelligent orchards. However, unstructured background, occlusion and dense berries make it challenging for grape yield estimation. We propose an efficient two-stage pipeline TSGYE: precise detection of grape clusters and efficient counting of grape berries.
Geng Deng +5 more
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Optimal solution of the two-stage Kalman estimator
Proceedings of 1995 34th IEEE Conference on Decision and Control, 1999The two-stage Kalman estimator was originally proposed to reduce the computational complexity of the augmented state Kalman filter. It was also applied to the tracking of maneuvering targets by treating the target acceleration as a bias term. Except in certain restrictive conditions, the conventional two-stage estimators are suboptimal in the sense ...
Hsieh, Chien-Shu, Chen, Fu-Chuang
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Two-stage estimation after parameter selection
2016 IEEE Statistical Signal Processing Workshop (SSP), 2016In many practical multiparameter estimation problems, no a-priori information exists regarding which parameters are more relevant within a group of candidate unknown parameters. This paper considers the estimation of a selected “parameter of interest”, where the selection is conducted according to a data-based selection rule, Ψ.
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On two-stage james-stein sstimators
Communications in Statistics. Part C: Sequential Analysis, 1983In the context of minimum risk (point) estimation of the mean vector of a multivariate normal distribution, based on the James-Stein and an allied rule, a two-stage procedure is considered, and the relative risk efficiency results are studied.
Ghosh, Malay, Sen, Pranab Kumar
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On Two–stage Estimate Based on Independent Estimate of Covariance Matrix
Acta Mathematica Sinica, English Series, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yin, Suju, Wang, Songgui
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Jackknifing the two stage least squares estimator
Communications in Statistics - Simulation and Computation, 1984A link is established between jackknifing smooth functions of regression parameter estimators in the general linear model and jackknifing the two stage least squares estimator in the simulta- neous equation model. Hinkley's weighted jackknife is explored and is shown to have a smaller variance than the standard jack- knife estimator in the context of ...
G. D. A. Phillips, B. P. McCabe
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two-stage least squares and the k-class estimator
1987Two-stage least squares (TSLS) is a method of estimating the parameters of a single structural equation in a system of linear simultaneous equations. The TSLS estimator was proposed by Theil (1953a, 1961) and independently by Basmann (1957). The early work on simultaneous equation estimation was carried out by a group of econometricians at the Cowles ...
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