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DETECTING OUTLIERS AND ASSERTING CONSISTENCY IN AGRICULTURE GROUND TRUTH INFORMATION BY USING TEMPORAL VI DATA FROM MODIS
Multi-temporal Image Processing Land Use Crop Mapping Image Understanding Satellite Remote Sensing
2015/12/31
Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then imp...
ROBUST METRIC STRUCTURE FROM MOTION FOR AN EXTENDED SEQUENCE WITH OUTLIERS AND MISSING DATA
structure from motion robust estimation projective reconstruction metric upgrade
2015/8/14
In this paper, we propose a robust metric structure from motion (SfM) algorithm for an extended sequence with outliers and missing
data. There are three main contributions in the proposed SfM algorit...
A spatial outlier is a spatial referenced object whose non-spatial attribute values are significantly different from those of other
spatially referenced objects in its spatial neighborhood. It repres...
A Geometric Analysis of Subspace Clustering with Outliers
Subspace clustering spectral clustering outlier detection `1 minimization duality in linear programming geometric functional analysis properties of convex bodies concentration of measure
2015/6/17
This paper considers the problem of clustering a collection of unlabeled data points assumed to lie near a union of lower dimensional planes. As is common in computer vision or unsupervised learning a...
Statistical Outliers and Dragon-Kings as Bose-Condensed Droplets
Statistical outliers Dragon-kings Physics and society Complex systems Bose-Einstein condensation Zipf law Power law
2012/6/5
A theory of exceptional extreme events, characterized by their abnormal sizes compared with the rest of the distribution, is presented. Such outliers, called "dragon-kings", have been reported in the ...
Modelling outliers and structural breaks in dynamic linear models with a novel use of a heavy tailed prior for the variances: An alternative to the Inverted Gamma
Modelling outliers structural breaks Inverted Gamma
2011/7/19
In this paper we propose a new wider class of hypergeometric heavy tailed priors that are given as the convolution of a Student-t density for the location parameter and a Scaled Beta2 prior for the va...
Outliers and patterns of outliers in contingency tables with Algebraic Statistics
Algebraic Statistics goodness-of-fi t tests log-linear mod-els toric models
2011/3/18
In this paper we provide a definition of pattern of outliers in contingency tables within a model-based framework. In particular, we make use of log-linear models and exact goodness-of-fit tests to sp...
Outliers in the spectrum of iid matrices with bounded rank perturbations
Outliers spectrum of iid matrices bounded rank perturbations
2011/2/24
It is known that if one perturbs a large iid random matrix by a bounded rank error, then the
majority of the eigenvalues will remain distributed according to the circular law. However, the bounded ra...
lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers
Best approximating subspace lp minimization as relaxation for l0 minimization
2011/3/3
We assume data sampled from a mixture of d-dimensional linear subspaces with outliers distributed symmetrically around the origin. We study the recovery of the global l0 subspace (i.e., with largest n...
Exploiting the information content of hydrological ''outliers'' for goodness-of-fit testing
information content hydrological outliers goodness-of-fit testing
2010/12/22
Validation of probabilistic models based on goodness-of-fit tests is an essential step for the frequency analysis of extreme events. The outcome of standard testing techniques, however, is mainly dete...
Outliers in INAR(1) models
integer-valued autoregressivemodels additive and innovational outliers conditionalleast squares estimators strong consistency
2010/3/19
In this paper the integer-valued autoregressive model of order one, contaminated with
additive or innovational outliers is studied in some detail. Moreover, parameter estimation
is also addressed. S...
Identifying outliers in Bayesian hierarchical models: a simulation-based approach
Hierarchical models diagnostics outliers distributional assumptions
2009/9/22
A variety of simulation-based techniques have been proposed for detec-
tion of divergent behaviour at each level of a hierarchical model. We investigate a
diagnostic test based on measuring the coni...
Dynamic factor models have a wide range of applications in econometrics and applied economics. The basic motivation resides in their capability of reducing a large set of time series to only few indic...
Propagation of outliers in multivariate data
Breakdown point contamination model independent contamination influence function robustness
2010/3/18
We investigate the performance of robust estimates of multivariate
location under nonstandard data contamination models such as
componentwise outliers (i.e., contamination in each variable is indepe...
PENALIZED TRIMMED SQUARES AND A MODIFICATION OF SUPPORT VECTORS FOR UNMASKING OUTLIERS IN LINEAR REGRESSION
robust regression mixed integer programming penalty method least trimmed squares identifying outliers support vector machines
2009/2/25
We consider the problem of identifying multiple outliers in linear regression models.
We propose a penalized trimmed squares (PTS) estimator, where penalty costs for discarding outliers are inserted ...