Optimal Randomness for Stochastic Configuration Network (SCN) with Heavy-Tailed Distributions [PDF]
Entropy, 2020 Stochastic Configuration Network (SCN) has a powerful capability for regression and classification analysis. Traditionally, it is quite challenging to correctly determine an appropriate architecture for a neural network so that the trained model can ...
Haoyu Niu, Jiamin Wei, YangQuan Chen
doaj +3 more sources
Fitting Heavy Tailed Distributions: The poweRlaw Package [PDF]
Journal of Statistical Software, 2015 Over the last few years, the power law distribution has been used as the data generating mechanism in many disparate fields. However, at times the techniques used to fit the power law distribution have been inappropriate.
Colin S. Gillespie
doaj +7 more sources
COVID-19 X-ray images classification based on enhanced fractional-order cuckoo search optimizer using heavy-tailed distributions. [PDF]
Appl Soft Comput, 2021 Classification of COVID-19 X-ray images to determine the patient’s health condition is a critical issue these days since X-ray images provide more information about the patient’s lung status.
Yousri D +5 more
europepmc +2 more sources
New discrete heavy tailed distributions as models for insurance data. [PDF]
PLoS ONE, 2023 Although many data sets are discrete and heavy tailed (for example, number of claims and claim amounts if recorded as rounded values), not many discrete heavy tailed distributions are available in the literature.
Saralees Nadarajah, Jiahang Lyu
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A New Class of Heavy-Tailed Distributions: Modeling and Simulating Actuarial Measures
Complexity, 2021 Statistical distributions play a prominent role for modeling data in applied fields, particularly in actuarial, financial sciences, and risk management fields.
Jin Zhao +4 more
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Extreme quantile estimation for partial functional linear regression models with heavy-tailed distributions. [PDF]
Can J Stat, 2022 In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy‐tailed distributions.
Zhu H, Li Y, Liu B, Yao W, Zhang R.
europepmc +2 more sources
Heavy-tailed distributions of confirmed COVID-19 cases and deaths in spatiotemporal space. [PDF]
PLoS ONE, 2023 This paper conducts a systematic statistical analysis of the characteristics of the geographical empirical distributions for the numbers of both cumulative and daily confirmed COVID-19 cases and deaths at county, city, and state levels over a time span ...
Peng Liu, Yanyan Zheng
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Heavy-tailed distributions, correlations, kurtosis and Taylor's Law of fluctuation scaling. [PDF]
Proc Math Phys Eng Sci, 2020 Pillai & Meng (Pillai & Meng 2016 Ann. Stat. 44, 2089–2097; p. 2091) speculated that ‘the dependence among [random variables, rvs] can be overwhelmed by the heaviness of their marginal tails ·· ·’. We give examples of statistical models that support this
Cohen JE, Davis RA, Samorodnitsky G.
europepmc +2 more sources
Sharp concentration results for heavy-tailed distributions [PDF]
Information and Inference: A Journal of the IMA, 2023 Abstract We obtain concentration and large deviation for the sums of independent and identically distributed random variables with heavy-tailed distributions. Our concentration results are concerned with random variables whose distributions satisfy $P(X>t) \leq{\text{ e}}^{- I(t)}$, where $I: \mathbb{R} \rightarrow \mathbb{R}$ is ...
Bakhshizadeh, Milad +2 more
openaire +4 more sources
Powerlaw: a Python package for analysis of heavy-tailed distributions. [PDF]
PLoS One, 2014 Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these ...
Alstott J, Bullmore E, Plenz D.
europepmc +3 more sources