Robust estimation
Subsampling Method for Robust Estimation of Regression Models
... Robust estimation and inference for regression models is an important problem with a long history in robust ...on robust regression is [3] which gives a thorough coverage of robust ...
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Robust Estimation of Similarity Transformation for Visual Object Tracking
... Most of existing correlation filter-based tracking approaches only estimate simple axis-aligned bounding boxes, and very few of them is capable of recovering the underlying similar- ity transformation. To tackle this ...
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Robust Estimation via Measurement Error Modeling
... Ultimately, our intention is to robustify inference in statistical models that are not easily robustified using standard approaches, such as time series models. It is such hard-to-robustify models that piqued our interest ...
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Robust estimation of stochastic gene network systems
... that robust state estimation using Kalman fil- tering techniques is ...the robust estimation scheme is analyzed based on the Ito’s theorem and Lyapunov stability ...
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Robust estimation of biometric data
... The estimation of covari- ance matrices is notoriously susceptible to outlier interference ...data. Robust estimation has seen a good amount of mathematical development start- ing from Hampel [5], ...
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Robust Estimation of Productivity Changes in Japanese Shinkin Banks
... Our data consist of annual data from the income statements of the shinkin banks from FY 2001 to FY 2008. The data come from the database of Nikkei NEED 3 . In the estimation of productivity changes, one difficulty ...
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Robust estimation with the weighted trimmed likelihood estimator
... parameter estimation in the presence of ...the robust weighted trimmed likelihood estimator (WTLE) to the standard GARCH ...additional robust parameter can be automatically ...introduced ...
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Robust estimation of hydrological model parameters
... Hydrological models are used for different purposes such as water management or flood forecasting. The estimation of hydrological model parameters is a difficult task. Rea- sons for this are the highly non-linear ...
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Robust Estimation for Fisher Discriminant Analysis
... Intuitively, [15] attempts to alleviate the sensitivity problem by assuming the, as of yet undened, worst-case estimation of the means and covariances of X and Y for optimizing the Fisher discrimi- nant ratio ...
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Robust estimation for structural time series models
... than the M—estimators are . There is a considerable shift in the sampling distributions of the MLEs resulting in significantly bigger biases . The mean square errors for the MLEs are also smaller than those for the ...
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A Robust Estimation Method for Camera Calibration with Known Rotation
... Both datasets are available online 3 , and include accurate camera matrices from which we extract the rotation matrices. The first dataset is the Fountain-P11, which contains eleven images of a fountain. The other ...
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Robust estimation : limit theorems and their applications
... The complexities inherrant in estimating parameters of a mixture of two normal distributions using minimal distance methods make it important to investigate applicability of these procedures in real data situations. ...
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Robust Estimation of Adaptive Deblurring Using Genetic Algorithm
... ABSTRACT: It is a quite difficult task to obtain images under dim conditions. There are many factors with which brightness of the image can be obtained, like the sensor sensitivity(ISO),Exposure time and Aperture. Due to ...
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Robust estimation of sulcal morphology
... the estimation of sulcal morphology in addition to standard measures such as cortical thickness, FreeSurfer and BrainVISA rely on different anatomical landmarks [45] which can yield differences in their resulting ...
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A Bayesian Method for Robust Estimation of Distributional Similarities
... The Bayesian estimation and the expectation calculation in Eq. 2 are generally difficult and usually require computationally expensive proce- dures. Since our motivation for this research is to calculate good ...
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Review on outlier tolerant data processing with applications
... minimax robust estimation of multivariate position vectors was given in Fan Jincheng and Hu Shaolin (1995), which solves the problem of fault-tolerant estimation of mean in the ergodic stationary ...
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The Jackknife and Multilevel Modeling: A New Application of an Old Trick
... Paper presented at the annual meeting of the American Educational Research Association, Montreal. Introduction to robust estimation and hypothesis testing[r] ...
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Simple robust parameter estimation for the Birnbaum-Saunders distribution
... parameter estimation and complete data without any contamination is always preferred to achieve a high accuracy on parameter ...study robust estimation for various distributions; see, for example, ...
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Unit Roots, Level Shifts and Trend Breaks in Per Capita Output: A Robust Evaluation
... (i) robust detection of breaks in the level and/or the slope of the trend function, (ii) robust estimation of the number of breaks, (iii) reliable inference regarding the presence of a unit root ...
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An Efficient and User Privacy-Preserving Routing Protocol for Wireless Mesh Networks
... with robust, reliable and efficient routing protocols so as to minimize the end-to-end ...accurate estimation of the available bandwidth in the wireless links and a robust estimation of the ...
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