Results 111 to 120 of about 37,630 (219)
Mathematical Finance, EarlyView.ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
wiley +1 more source
The computation of case fatality rate for novel coronavirus (COVID-19) based on Bayes theorem: An observational study. [PDF]
Medicine (Baltimore), 2020 Chang CS +5 more
europepmc +1 more source
Is A Little Learning Dangerous?
Noûs, EarlyView.ABSTRACT I argue that a little learning is often dangerous even for ideal reasoners who are operating in extremely simple scenarios and know all the relevant facts about how the evidence is generated. More precisely, I show that, on many plausible ways of assigning value to a credence in a hypothesis H, ideal Bayesians should sometimes expect other ...
Bernhard Salow
wiley +1 more source
Weighted naïve bayes multi-user classification for adaptive authentication
Journal of Physics CommunicationsMachine learning classification algorithms have been extensively utilized in addressing user authentication challenges. Nonetheless, a majority of solutions categorize users into three classes, whereas adaptive authentication scenarios necessitate ...
Prudence M Mavhemwa +3 more
doaj +1 more source
Assessing the Effectiveness of Workers' Selection Exams: The Case of the Bank of Italy
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT High‐stakes exams can be used to rank and select candidates for job openings, and the ability of those selected hinges on the design of the exam. I propose a method to model candidates' performance to assess how effective the exam is at selecting high‐ability candidates.
Santiago Pereda‐Fernández
wiley +1 more source
The Astrophysical Journal Supplement SeriesDetecting oscillations in solar and stellar time series is complicated by nonstationary red noise and evolving background emission. Methods based on detrending and AR(1)-based wavelet analysis can introduce spurious periodicities and do not adequately ...
Song Feng, Lin Li, Ding Yuan
doaj +1 more source
Circular inference in visual cortical hierarchies in schizophrenia
Psychiatry and Clinical Neurosciences, EarlyView.Aim In schizophrenia, disrupted perceptual processes contribute to positive symptoms. However, it remains unclear how top‐down priors and bottom‐up likelihoods are represented across the hierarchy of visual cortices. To identify these processes within cortical hierarchies, the circular inference model offers a framework to account for the biased ...
Shuhei Hara +7 more
wiley +1 more source
Simulations All the Way Up! An Atheist's Response to the Fine‐Tuning Argument
Analytic Philosophy, EarlyView.ABSTRACT So the Fine‐tuning Argument goes, because it is so unlikely for the physical constants of the laws of nature to have taken the values that they in fact take, we should significantly raise our credence that God exists. Simulation Arguments argue that our world might be (or, in stronger versions, that it probably is) a mere computer simulation ...
Nikk Effingham
wiley +1 more source
Bayes Theorem and Protopathic Bias: Methodological Concerns When Addressing the Impact of Fetal Heart Rate Patterns on the Cesarean Section Rate. [PDF]
AJP Rep, 2020 Balayla J +3 more
europepmc +1 more source
Sparse Minimum Redundancy Maximum Relevance for Feature Selection
Scandinavian Journal of Statistics, EarlyView.ABSTRACT We propose a feature screening method that integrates both feature–feature and feature–target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classical mRMR penalized by a non‐convex regularizer, and where the parameters estimated as ...
Peter Naylor +3 more
wiley +1 more source