Results 151 to 160 of about 1,294,144 (288)
Unconditional Variance Estimation Under Complex Surveys
International Statistical Review, EarlyView.Summary The unconditional framework treats the samples and the variables of interest as random variables. This is particularly suitable with analytic inference, when modelling survey data. We show that variance estimation does not involve finite population corrections and joint‐inclusion probabilities, even with large sampling fractions and under ...
Yves G. Berger
wiley +1 more source
Experimental probabilistic pragmatics beyond Bayes’ theorem
Zeitschrift für Sprachwissenschaft, 2016 Pfeifer Niki
doaj +1 more source
Journal of Advanced Nursing, EarlyView.ABSTRACT Aim To examine the impact of delays in intensive care unit (ICU) admission on patient outcomes, specifically clinical deterioration and mortality among patients transferred from the emergency department (ED) or general wards following acute deterioration in an Australian public hospital.
Shivaprasad Anagi +8 more
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
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
Do robots boost productivity? A quantitative meta‐study
Journal of Economic Surveys, EarlyView.ABSTRACT This meta‐study analyzes the productivity effects of industrial robots. More than 1800 estimates from 85 primary studies are collected. The meta‐analytic evidence suggests that robotization has so far provided, at best, a small boost to productivity. There is strong evidence of publication bias in the positive direction.
Florian Schneider
wiley +1 more source
Markov Determinantal Point Process for Dynamic Random Sets
Journal of Time Series Analysis, EarlyView.ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley +1 more source
Multiple Chains Markov Switching Vector Autoregression
Journal of Time Series Analysis, EarlyView.ABSTRACT Both the U.S. stock and bond returns exhibit distinct Markovian regimes. However, because these regimes display limited coherence, conventional models typically require highly parameterized systems to adequately capture their joint distribution.
Leopoldo Catania
wiley +1 more source
Why Do Prosocial People Dislike Markets in Some Countries and Like Them in Others?
Kyklos, EarlyView.ABSTRACT Based on the doux commerce thesis, which suggests that people in market‐oriented societies hold stronger prosocial values than those in less market‐oriented ones, one can expect prosocial and pro‐market values to be positively associated. The fact that the association holds for cross‐country observations but does not universally hold for cross‐
Pál Czeglédi
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