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pro vyhledávání: '"Kenric P. Nelson"'
Autor:
Kenric P. Nelson
Publikováno v:
Entropy, Vol 26, Iss 2, p 118 (2024)
Nonextensive statistical mechanics has developed into an important framework for modeling the thermodynamics of complex systems and the information of complex signals. To mark the 80th birthday of the field’s founder, Constantino Tsallis, a review
Externí odkaz:
https://doaj.org/article/831e9545ad13492cb9454a25f3ab54a1
Publikováno v:
Entropy, Vol 24, Iss 3, p 423 (2022)
We present a coupled variational autoencoder (VAE) method, which improves the accuracy and robustness of the model representation of handwritten numeral images. The improvement is measured in both increasing the likelihood of the reconstructed images
Externí odkaz:
https://doaj.org/article/1d3ea0fa451541c8a91d20a82d5ebcb5
Publikováno v:
Proceedings of the National Academy of Sciences. 119
We investigate the financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize the individuals in a financial market by their trading strategy, namely noise traders and fundamentalists. The
Publikováno v:
Entropy, Vol 13, Iss 8, Pp 1518-1532 (2011)
E.T. Jaynes, originator of the maximum entropy interpretation of statistical mechanics, emphasized that there is an inevitable trade-off between the conflicting requirements of robustness and accuracy for any inferencing algorithm. This is because ro
Externí odkaz:
https://doaj.org/article/4fc82f3c82ce44aabf496b5244ce07cf
Publikováno v:
Physica A: Statistical Mechanics and its Applications. 515:762-770
We use a heterogeneous agent-based two-state sociophysics model to simulate financial markets. Focusing on stock market trader dynamics, we propose a model with two kinds of individual – the contrarian agent and the noise trader – in which the dy
Autor:
Kenric P. Nelson
Publikováno v:
Entropy, Vol 19, Iss 6, p 286 (2017)
An approach to the assessment of probabilistic inference is described which quantifies the performance on the probability scale. From both information and Bayesian theory, the central tendency of an inference is proven to be the geometric mean of the
Externí odkaz:
https://doaj.org/article/81f30d2b7fb54050b5b17763d672201b
Autor:
Kenric P. Nelson
Publikováno v:
Physica A: Statistical Mechanics and its Applications. 601:127574
A new statistical estimation method, Independent Approximates (IAs), is defined and proven to enable closed-form estimation of the parameters of heavy-tailed distributions. Given independent, identically distributed samples from a one-dimensional dis
Autor:
Kenric P. Nelson
This chapter introduces a simple, intuitive approach to the assessment of probabilistic inferences. The Shannon information metrics are translated to the probability domain. The translation shows that the negative logarithmic score and the geometric
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b0cf599331efcc3a6696abd7de4b79a
https://doi.org/10.1093/oso/9780190636685.003.0012
https://doi.org/10.1093/oso/9780190636685.003.0012
Publikováno v:
Physica A: Statistical Mechanics and its Applications. 588:126527
We propose a three-state microscopic opinion formation model for the purpose of simulating the dynamics of financial markets. In order to mimic the heterogeneous composition of the mass of investors in a market, the agent-based model considers two di
Publikováno v:
Fractional Calculus and Applied Analysis. 21:336-353