scholarly journals Domains of weak continuity of statistical functionals with a view toward robust statistics

2017 ◽  
Vol 158 ◽  
pp. 1-19 ◽  
Author(s):  
Volker Krätschmer ◽  
Alexander Schied ◽  
Henryk Zähle
Keyword(s):  
Robust Statistics ◽  
Weak Continuity ◽  
Statistical Functionals

scholarly journals Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1250
Author(s):  
Daniel Medina ◽  
Haoqing Li ◽  
Jordi Vilà-Valls ◽  
Pau Closas
Keyword(s):  
Intelligent Transportation Systems ◽  
Robust Statistics ◽  
Real Data ◽  
Transportation Systems ◽  
Global Navigation Satellite Systems ◽  
Mixed Integer ◽  
Robust Filtering ◽  
Precise Positioning ◽  
The Impact ◽  
Filtering Techniques

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

scholarly journals Roberts’ weak welfarism theorem: a minor correction

2021 ◽  
Author(s):  
Peter J. Hammond
Keyword(s):  
Euclidean Space ◽  
Social Welfare ◽  
Utility Function ◽  
Weak Continuity ◽  
Strict Preference ◽  
Counter Example ◽  
Independence Of Irrelevant Alternatives ◽  
Unrestricted Domain ◽  
A Minor ◽  
Minor Correction

AbstractRoberts’ “weak neutrality” or “weak welfarism” theorem concerns Sen social welfare functionals which are defined on an unrestricted domain of utility function profiles and satisfy independence of irrelevant alternatives, the Pareto condition, and a form of weak continuity. Roberts (Rev Econ Stud 47(2):421–439, 1980) claimed that the induced welfare ordering on social states has a one-way representation by a continuous, monotonic real-valued welfare function defined on the Euclidean space of interpersonal utility vectors—that is, an increase in this welfare function is sufficient, but may not be necessary, for social strict preference. A counter-example shows that weak continuity is insufficient; a minor strengthening to pairwise continuity is proposed instead and its sufficiency demonstrated.

scholarly journals Confirming known planetary trends using a photometrically selected Kepler sample

2020 ◽  
Author(s):  
Jonah T Hansen ◽  
Luca Casagrande ◽  
Michael J Ireland ◽  
Jane Lin
Keyword(s):  
Sample Size ◽  
Robust Statistics ◽  
Narrow Band ◽  
Small Sample Size ◽  
Small Sample ◽  
Fitting Algorithm ◽  
Statistical Studies ◽  
The Rich ◽  
Host Stars ◽  
High Metallicity

Abstract Statistical studies of exoplanets and the properties of their host stars have been critical to informing models of planet formation. Numerous trends have arisen in particular from the rich Kepler dataset, including that exoplanets are more likely to be found around stars with a high metallicity and the presence of a “gap” in the distribution of planetary radii at 1.9 R⊕. Here we present a new analysis on the Kepler field, using the APOGEE spectroscopic survey to build a metallicity calibration based on Gaia, 2MASS and Strömgren photometry. This calibration, along with masses and radii derived from a Bayesian isochrone fitting algorithm, is used to test a number of these trends with unbiased, photometrically derived parameters, albeit with a smaller sample size in comparison to recent studies. We recover that planets are more frequently found around higher metallicity stars; over the entire sample, planetary frequencies are 0.88 ± 0.12 percent for [Fe/H] < 0 and 1.37 ± 0.16 percent for [Fe/H] ≥ 0 but at two sigma we find that the size of exoplanets influences the strength of this trend. We also recover the planet radius gap, along with a slight positive correlation with stellar mass. We conclude that this method shows promise to derive robust statistics of exoplanets. We also remark that spectrophotometry from Gaia DR3 will have an effective resolution similar to narrow band filters and allow to overcome the small sample size inherent in this study.

scholarly journals Editorial, special issue on “Advances in Robust Statistics”

METRON ◽  
2021 ◽  
Author(s):  
Marco Riani ◽  
Mia Hubert
Keyword(s):  
Statistical Methods ◽  
Robust Statistics ◽  
Statistical Analyses ◽  
Striking Feature ◽  
Special Issue ◽  
Current State ◽  
Editorial Special Issue ◽  
Data Points ◽  
Robust Statistical Methods

AbstractStarting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.

scholarly journals Design of a Didactical Activity for the Analysis of Uncertainties in Thermography through the Use of Robust Statistics as Teacher-Oriented Approach

2021 ◽  
Vol 13 (3) ◽  
pp. 402
Author(s):  
Pablo Rodríguez-Gonzálvez ◽  
Manuel Rodríguez-Martín
Keyword(s):  
Open Source ◽  
Robust Statistics ◽  
Three Dimensional ◽  
Learning Material ◽  
Novel Approach ◽  
Learning Programs ◽  
Institutional Learning ◽  
Thermographic Image ◽  
Visualization Techniques ◽  
Free Open Source

The thermography as a methodology to quantitative data acquisition is not usually addressed in the degrees of university programs. The present manuscript proposes a novel approach for the acquisition of advanced competences in engineering courses associated with the use of thermographic images via free/open-source software solutions. This strategy is established from a research based on the statistical and three-dimensional visualization techniques over thermographic imagery to improve the interpretation and comprehension of the different sources of error affecting the measurements and, thereby, the conclusions and analysis arising from them. The novelty is focused on the detection of non-normalities in thermographic images, which is illustrates in the experimental section. Additionally, the specific workflow for the generation of learning material related with this aim is raised for asynchronous and e-learning programs. These virtual materials can be easily deployed in an institutional learning management system, allowing the students to work with the models by means of free/open-source solutions easily. Subsequently, the present approach will give new tools to improve the application of professional techniques, will improve the students’ critical sense to know how to interpret the uncertainties in thermography using a single thermographic image, therefore they will be better prepared to face future challenges with more critical thinking.

MAAPER: model-based analysis of alternative polyadenylation using 3' end-linked reads

2021 ◽  
Author(s):  
Wei Vivian Li ◽  
Dinghai Zheng ◽  
Ruijia Wang ◽  
Bin Tian
Keyword(s):  
Single Cell ◽  
Robust Statistics ◽  
Single Cell Analysis ◽  
Alternative Polyadenylation ◽  
Computational Method ◽  
Model Based ◽  
Eukaryotic Genes ◽  
Counting Strategy ◽  
Cleavage And Polyadenylation ◽  
Model Based Analysis

Most eukaryotic genes harbor multiple cleavage and polyadenylation sites (PASs), leading to expression of alternative polyadenylation (APA) isoforms. APA regulation has been implicated in a diverse array of physiological and pathological conditions. While RNA sequencing tools that generate reads containing the PAS, named onSite reads, have been instrumental in identifying PASs, they have not been widely used. By contrast, a growing number of methods generate reads that are close to the PAS, named nearSite reads, including the 3' end counting strategy commonly used in single cell analysis. How these nearSite reads can be used for APA analysis, however, is poorly studied. Here, we present a computational method, named model-based analysis of alternative polyadenylation using 3' end-linked reads (MAAPER), to examine APA using nearSite reads. MAAPER uses a probabilistic model to predict PASs for nearSite reads with high accuracy and sensitivity, and examines different types of APA events, including those in 3'UTRs and introns, with robust statistics. We show MAAPER's accuracy with data from both bulk and single cell RNA samples and its applicability in unpaired or paired experimental designs. Our result also highlights the importance of using well annotated PASs for nearSite read analysis.

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