Results 291 to 300 of about 1,618,729 (319)
Self-supervised learning enhances accuracy and data efficiency in lower-limb joint moment estimation from gait kinematics. [PDF]
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On the robustness of two-stage estimators
Statistics & Probability Letters, 2012a b s t r a c t The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general two-stage Mestimator, and provide their interpretations.
Zhelonkin, Mikhail +2 more
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On a Two-Stage Estimate of the Mean
Journal of the American Statistical Association, 1971Abstract A two-stage estimate for the mean vector of a multivariate distribution is proposed for the situation in which the prior knowledge about the mean vector can be expressed in the form of an initial estimate. The proposed estimate is compared with the sample mean based on a single sample of equivalent size.
S. K. Katti, V.B. Waikar
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Two Stage Estimation in Data Processing [PDF]
2008 International Symposium on Intelligent Information Technology Application Workshops, 2008 The new method presented in this paper shows an effective way of solving an estimation problem, the estimated values are nearer to their theoretical ones than in an adjustment with the method of least squares. Considering the semi parametric adjustment models, firstly, the estimators of the parameters and the nonparametric are derived by using a kernel
Chen Gang, Pan Xiong, Chen Yu
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Estimation in flexible two stage designs
Statistics in Medicine, 2006Adaptive test designs for clinical trials allow for a wide range of data driven design adaptations using all information gathered until an interim analysis. The basic principle is to use a test statistics which is invariant with respect to the design adaptations under the null hypothesis.
Werner Brannath +2 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 ...
Fu-Chuang Chen, Chien-Shu Hsieh
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Australian & New Zealand Journal of Statistics, 2005
SummaryThis paper presents a two‐stage procedure for estimating the conditional support curve of a random variable X, given the information of a random vector X. Quantile estimation is followed by an extremal analysis on the residuals for problems which can be written as regression models.
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SummaryThis paper presents a two‐stage procedure for estimating the conditional support curve of a random variable X, given the information of a random vector X. Quantile estimation is followed by an extremal analysis on the residuals for problems which can be written as regression models.
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A Two‐Stage Stepwise Estimation Procedure
Biometrics, 2008Summary This article proposes a two‐stage simultaneous confidence procedure for the comparisons of k pairs of population means, without using multiplicity adjustment of more than two populations. The proposed procedure can be broadly applied to parametric or nonparametric models.
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Two Stages Liu Regression Estimator
Communications in Statistics - Simulation and Computation, 2015This paper introduces a new estimator for multicollinearity and autocorrelated errors. We propose the Two Stages Liu estimator (TL) for the multiple linear regression model which suffers from autocorrelation AR(1) and multicollinearity problems. We use a mixed method to apply the two stages least squares procedure (TS) for deriving the TL estimator. We
Issam Dawoud, Selahattin Kaçıranlar
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