Results 61 to 70 of about 2,939,863 (258)
Conditional stochastic dominance tests in dynamic settings [PDF]
, 2014 This paper proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests lies in the nonparametric manner of incorporating the information set.
Jose Olmo +5 more
core +1 more source
Around the Probability Distribution of The Estimated Random Ridge Factor with Stochastic Prior Information [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 In this paper, The probability distribution of the estimated stochastic ridge factor has been found, which has been developed by adding prior information to the sample information.
doaj +1 more source
“Smelltronics”—From Gas to Smell Sensing
Advanced Materials, EarlyView.The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono +7 more
wiley +1 more source
Artificial Intelligence Meets Micro/Nanorobotics
Advanced Materials, EarlyView.Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever +6 more
wiley +1 more source
Modelling the operation of multireservoir systems using decomposition and stochastic dynamic programming [PDF]
, 2006 Stochastic dynamic programming models are attractive for multireservoir control problems because they allow non-linear features to be incorporated and changes in hydrological conditions to be modeled as Markov processes.
Archibald, Thomas W.; id_orcid +5 more
core +1 more source
An improved bootstrap test of stochastic dominance [PDF]
, 2009 We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the ...
Song, Kyungchul +2 more
core +2 more sources
Forecasting college football game outcomes using modern modeling techniques
Journal of Sports Analytics, 2020 There are many reasons why data scientists and fans of college football would want to forecast the outcome of games – gambling, game preparation and academic research, for example. As advanced statistical methods become more readily accessible, so do the
Charles South, Edward Egros
doaj +1 more source
Advanced Materials, EarlyView.Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh +5 more
wiley +1 more source
The Distribution of Stochastic Shrinkage Parameters in Ridge Regression [PDF]
In this article we derive the density and distribution functions of the stochastic shrinkage parameters of three well-known operational Ridge Regression estimators by assuming normality. The stochastic behavior of these parameters is likely to affect the
Luis Firinguetti, Hernán Rubio
core
Machine learning regression models for internal shame
Acta PsychologicaThis study aims to predict Internal Shame (IS) based on childhood trauma, social emotional competence, cognitive flexibility, distress tolerance and alexithymia in an Iranian sample.
Nataša Kovač +3 more
doaj +1 more source