Results 11 to 20 of about 16,679,614 (365)
Instance-Based Classification Through Hypothesis Testing
IEEE Access, 2021 Classification is a fundamental problem in machine learning and data mining. During the past decades, numerous classification methods have been presented based on different principles. However, most existing classifiers cast the classification problem as
Zengyou He +3 more
doaj +1 more source
Hypothesis Testing in Econometrics [PDF]
SSRN Electronic Journal, 2009 This article reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including finite-sample and large-sample optimality. Then, we summarize some of the most important methods, as well as resampling methodology, which is useful to set ...
Romano, Joseph P +2 more
openaire +7 more sources
Privacy-Aware Distributed Hypothesis Testing
Entropy, 2020 A distributed binary hypothesis testing (HT) problem involving two parties, a remote observer and a detector, is studied. The remote observer has access to a discrete memoryless source, and communicates its observations to the detector via a rate-limited
Sreejith Sreekumar +2 more
doaj +1 more source
Testing the Omnivore Hypothesis in Russia
Monitoring Obŝestvennogo Mneniâ: Ekonomičeskie i Socialʹnye Peremeny, 2021 In the last thirty years, a significant shift from the homology to omnivore argument has occurred in musical preference studies. Studies on the omnivore argument mainly come from North and South America, Western and sometimes Eastern Europe.
Юлия Олеговна Папушина
doaj +1 more source
Score-Based Hypothesis Testing for Unnormalized Models
IEEE Access, 2022 Unnormalized statistical models play an important role in machine learning, statistics, and signal processing. In this paper, we derive a new hypothesis testing procedure for unnormalized models. Our approach is motivated by the success of score matching
Suya Wu +4 more
doaj +1 more source
Circulation, 2006 In most biomedical research, investigators hypothesize about the relationships of various factors, collect data to test those relationships, and try to draw conclusions about those relationships from the data collected. In many cases, investigators test relationships by comparing the average level of a factor between 2 groups or between 1 group and a ...
Roger B. Davis, Kenneth J. Mukamal
openaire +7 more sources
Entropy, 2016 The extraordinary success of physicists to find simple laws that explain many phenomena is beguiling. With the exception of quantum mechanics, it suggests a deterministic world in which theories are right or wrong, and the world is simple.
Joseph B. Kadane
doaj +1 more source
Current controversies: Null hypothesis significance testing
Acta Obstetricia et Gynecologica Scandinavica, 2022 Traditional null hypothesis significance testing (NHST) incorporating the critical level of significance of 0.05 has become the cornerstone of decision‐making in health care, and nowhere less so than in obstetric and gynecological research. However, such
Philip M. Sedgwick +3 more
doaj +1 more source
Non-Stochastic Hypothesis Testing with Application to Privacy Against Hypothesis-Testing Adversary [PDF]
, 2019 In this paper, we consider privacy against hypothesis testing adversaries within a non-stochastic framework. We develop a theory of non-stochastic hypothesis testing by borrowing the notion of uncertain variables from non-stochastic information theory ...
Farokhi, Farhad
core +2 more sources
Quantum hypothesis testing in many-body systems
SciPost Physics Core, 2021 One of the key tasks in physics is to perform measurements in order to determine the state of a system. Often, measurements are aimed at determining the values of physical parameters, but one can also ask simpler questions, such as "is the system in ...
Jan de Boer, Victor Godet, Jani Kastikainen, Esko Keski-Vakkuri
doaj +1 more source