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Robust Statistics

A 3D interactive multi-object segmentation tool using local robust statistics driven active contours

A 3D interactive multi-object segmentation tool using local robust statistics driven active contours

... local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation ...

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A robust statistics driven volume-scalable active contour for segmenting anatomical structures in volumetric medical images with complex conditions

A robust statistics driven volume-scalable active contour for segmenting anatomical structures in volumetric medical images with complex conditions

... Currently we only use certain local robust statistics for image features extraction. How- ever, the proposed volume-scalable method provides a basic scheme into which more sophisticated image features can ...

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The Application of Robust Statistics to China’s Stock Market

The Application of Robust Statistics to China’s Stock Market

... and robust statistics method (RSM) can over- come the influence on the final result under the condition that data will not be deleted, which is a useful multivariate analysis method for exploratory analysis ...

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A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics

A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics

... Strict liability pertaining to defective products in Germany is regulated by the German Product Liability Act. 581[r] ...

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Robust Statistics Analysis and Difference Significance Test of the Test Data of Laboratory Proficiency Testing

Robust Statistics Analysis and Difference Significance Test of the Test Data of Laboratory Proficiency Testing

... called robust statistical Z-Score, and a statistical analysis of the results was done with the application of SPSS software, F test was applied to the results which were divided into different groups according to ...

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Robust statistics using Stata

Robust statistics using Stata

... Prob > F = 0 0 0. 0 . .0 . 0 00 0 00 0 0 0 0 00 0 0 0 F( 5, 94) = 3 3 33 3 3 3. 3 .2 . . 2 2 28 8 8 8 Robust regression Number of obs = 1 1 10 1 0 0 00 0 0 0 Biweight iteration 5: maximum difference in weights ...

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Amazing journey to robust statistics, discovering outliers for efficient prediction

Amazing journey to robust statistics, discovering outliers for efficient prediction

... Hence robust BG test which is not much affected by high leverage points is proposed for the detection of autocorrelated errors in multiple linear regression (Lim and Midi, 2012; Lim and [r] ...

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Robust PCA and Robust Linear Regression via Sparsity Regularization

Robust PCA and Robust Linear Regression via Sparsity Regularization

... of robust linear regression is to accurately estimate the model parameter in the presence of these troublesome ...Many robust estimators [5]–[7] have been developed in the spirit of Robust ...

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A Monte Carlo Comparison of Robust MANOVA Test Statistics

A Monte Carlo Comparison of Robust MANOVA Test Statistics

... test statistics that can be considered including robust statistics and the use of the structural equation modeling (SEM) ...test statistics with fifteen other test statistics across ...

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Robust Toll Pricing

Robust Toll Pricing

... studies where robust optimization framework is applied to pricing problems, in Violin (2014) and Gardner et al. (2010). In both these works the models considered are different from our model and problem setting. ...

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Robust Variable Selection

Robust Variable Selection

... I think it is most appropriate to start by thanking my advisors Dr. Dennis Boos and Dr. Leonard Stefanski. I have a great amount of respect not only for the con- tributions they have made to the field of ...

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Robust Hierarchical Clustering

Robust Hierarchical Clustering

... One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational biology to social sciences to computer ...

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Robust Synthetic Control

Robust Synthetic Control

... The factor models that are commonly used in the Econometrics literature, cf. Abadie et al. (2010, 2011); Abadie and Gardeazabal (2003), often lead to a low rank structure for the underlying mean matrix M . When f is ...

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Order Statistics. Lecture 15: Order Statistics. Notation Detour. Order Statistics, cont.

Order Statistics. Lecture 15: Order Statistics. Notation Detour. Order Statistics, cont.

... If we imagine that the running speed in m/s of competitive sprinters is given by an Exponential distribution with.. λ = 1.[r] ...

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Statistics Elective 3.00 (MATH 211 Statistics with Aviation or MATH 222 Business Statistics.

Statistics Elective 3.00 (MATH 211 Statistics with Aviation or MATH 222 Business Statistics.

... Science, Aviation Maintenance, Air Traffic Control, Safety. College credit by examination may apply. Visit the ERAU website for a description of courses available.)... Upper Level Free E[r] ...

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Court statistics 2013 Official statistics of Sweden

Court statistics 2013 Official statistics of Sweden

... These statistics are divided into three chapters, each of which begins with a summary of the work of each court ...presents statistics from the general courts, ...whilst statistics from the general ...

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Robust Gram Embeddings

Robust Gram Embeddings

... a robust behaviour under small sample size situations, sample perturbations and it reaches a higher word similarity performance compared to its ...from Robust Gram increases notably as diverse test sets are ...

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Robust  Pseudorandom  Generators

Robust Pseudorandom Generators

... strong robust -biased PRG, we construct the other PRG as ...strong robust -biased PRG for linear tests with large ...strong robust r-wise independent PRG, we obtain a strong robust -biased ...

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Robust Logo Watermarking

Robust Logo Watermarking

... and robust against various attacks such as cropping, low- pass filtering, scaling, median filtering, the addition of white noise, as well as JPEG and JPEG2000 compression at high compression ...

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Robust Correlation Clustering

Robust Correlation Clustering

... In this section, we show two simple but illuminating results. The first result explains how, in contrast to problems like k-median and k-means, the vanilla correlation clustering objective is in fact inherently ...

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