Fixed-Confidence, Fixed-Tolerance Guarantees for Ranking-and-Selection Procedures

Ever since the conception of the statistical ranking-and-selection (R8S) problem, a predominant approach has been the indifference-zone (IZ) formulation. Under the IZ formulation, R8S procedures are designed to provide a guarantee on the probability of correct selection (PCS) whenever the performance of the best system exceeds that of the second-best system by a specified amount. We discuss the shortcomings of this guarantee and argue that providing a guarantee on the probability of good selection (PGS)—selecting a system whose performance is within a specified tolerance of the best—is a more justifiable goal. Unfortunately, this form of fixed-confidence, fixed-tolerance guarantee has received far less attention within the simulation community. We present an overview of the PGS guarantee with the aim of reorienting the simulation community toward this goal. We examine numerous techniques for proving the PGS guarantee, including sufficient conditions under which selection and subset-selection procedures that deliver the IZ-inspired PCS guarantee also deliver the PGS guarantee.

RANKING OF DAILY SATELLITE-DERIVED PRECIPITATION EXTREMES FOR THE ORBIG PIPELINE IN RIO DE JANEIRO

The present work was motivated by the occurrence of vast damage caused by intense rainfalls in the state of Rio de Janeiro and the great importance of the oil pipelines for the economy by using remote sensing multisatellite dataset from the GPM 3-IMERG-HHE product from 06/2000 to 06/2019, along the ORBIG pipeline located between the municipalities of Angra dos Reis and Duque de Caxias, RJ. A statistical ranking method has been applied to classify extreme daily precipitation events over the region. An event is classified as extreme by considering the total affected area and its intensity, based on the daily normalized anomaly calculated from the climatology data. The results show that in cold front events the oil pipeline region is hit more spatially with high accumulations of daily precipitation. However, in thermal instability precipitation, despite affecting locally, it has also shown extreme precipitation events, highlighting that in the 10 largest cases there were no false alarms, according to records found in news reports and rainfall indexes. It was also noted that during summer time there were more extreme cases. In conclusion, this study served to indicate places and times of higher rainfall index regardless of whether the region has a dense population or not.

Statistical ranking of electromechanical dyssynchrony parameters for CRT

ObjectiveMechanical evaluation of dyssynchrony by echocardiography has not replaced ECG in routine cardiac resynchronisation therapy (CRT) evaluation because of its complexity and lack of reproducibility. The objective of this study was to evaluate the potential correlations between electromechanical parameters (atrioventricular, interventricular and intraventricular from the dyssynchrony model presented in 2000), their ability to describe dyssynchrony and their potential use in resynchrony.Methods455 sets of the 18 parameters of the model obtained in 91 patients submitted to various pacing configurations were evaluated two by two using a Pearson correlation test and then by groups according to their ability to describe dyssynchrony, using the Column selection method of machine learning.ResultsThe best parameter is duration of septal contraction, which alone describes 25% of dyssynchrony. The best groups of 3, 4 and ≥8 variables describe 59%, 73% and almost 100% of dyssynchrony, respectively. Left pre-ejection interval is highly and significantly correlated to a maximum of other variables, and its decrease is associated with the favourable evolution of all other correlated parameters. Increase in filling duration and decrease in duration of septum to lateral wall contraction difference are not associated with the favourable evolution of other parameters.ConclusionsNo single electromechanical parameter alone can fully describe dyssynchrony. The 18-parameter model can be simplified, but still requires at least 4–8 parameters. Decrease in left pre-ejection interval favourably drives resynchrony in a maximum of other parameters. Increase in filling duration and decrease in septum–lateral wall difference do not appear to be good CRT targets.

The RNPLS&T’s Science Archive Portal in the scientific communication system

Scientific communication infrastructure is examined by the example of the Russian National Public Library for Science and Technology. The functional features of RNPLS&T’s Science Archive are discussed. Types of scientific works to be indexed via the portal are presented.Statistics of the Science Archive representation is given, and the metadata being stored is characterized. The author analyzes the ranking methods for academic works, and cites statistical ranking data for different types of scientific works, e. g. articles or learning aids, etc. The МоngoDB DBMS makes the technological foundation for the Science Archive. Academic works indices, user account data, database retrieval data, metadata of academic works indexed by the Internet search servers are implemented and operate in compliance with the Open Access protocols. The depositing functionality is licensed to the Science Archive by a copyright owner. The author concludes that in the information and technological society a common researcher and a prominent scientists may lack the communication environment. This evidences that the Science Archive and similar portals make the essential part of the vast science environment.

Do Mutual Funds Attract the Right Investor? A Stochastic Dominance Approach

Decision theory is concerned with identifying values and uncertainties in a given decision that result in the optimal outcome (Wald, 1939). It is one of the core aspects of any financial or investment decision. We consider the case where the investor has the choice between a passive index (such as a market index) and an actively managed mutual fund. Our analysis aims to determine which option an investor will choose based on a statistical ranking method known as stochastic dominance. We then evaluate this choice against the background information supplied by the mutual fund to ascertain whether the choice given by stochastic dominance is indeed in line with the investor profile given by the mutual fund. It is found that of the 11 mutual funds examined over the sample period of April 2006 to April 2013, only 4 attract the correct type of investor, 3 attract a mixture of investors and 4 attract (arguably) the wrong type of investor.