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A connection between fractional calculus and statistical distribution theory has been established by the authors recently. Some extensions of the results to matrix-variate functions were also considered. In the present article, more results…

Statistical Mechanics · Physics 2011-03-01 A. M. Mathai , H. J. Haubold

We establish properties of a new type of fractal which has partial self similarity at all scales. For any collection of iterated functions systems with an associated probability distribution and any positive integer V there is a…

Dynamical Systems · Mathematics 2008-02-04 Michael Barnsley , John E. Hutchinson , Örjan Stenflo

If two random variables X and A are functionally related via f(X)=A for some strictly monotone continuously differentiable function f:R->R, the distribution of X may easily be computed from the distribution of A.

General Mathematics · Mathematics 2022-08-16 Kerry Michael Soileau

The characteristic function of the folded normal distribution and its moment function are derived. The entropy of the folded normal distribution and the Kullback--Leibler from the normal and half normal distributions are approximated using…

Methodology · Statistics 2014-02-17 Michail Tsagris , Christina Beneki , Hossein Hassani

The present paper studies the limiting behavior of the average score of a sequentially selected group of items or individuals, the underlying distribution of which, $F$, belongs to the Gumbel domain of attraction of extreme value…

Probability · Mathematics 2010-11-16 Abba M. Krieger , Moshe Pollak , Ester Samuel-Cahn

The efficient modeling for disorder in a phenomena depends on the chosen score and objective functions. The main parameters in modeling are location, scale and shape. The exponential power distribution known as generalized Gaussian is…

Statistics Theory · Mathematics 2021-02-08 Mehmet Niyazi Çankaya

In many statistical problems, the data distribution is specified through a generative process for which the likelihood function is analytically intractable, yet inference on the associated model parameters remains of primary interest. We…

Methodology · Statistics 2026-04-01 Haoyu Jiang , Yuexi Wang , Yun Yang

Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are…

Quantitative Methods · Quantitative Biology 2010-10-22 Vladimir Trifonov , Laura Pasqualucci , Riccardo Dalla-Favera , Raul Rabadan

For analysis of a high-dimensional dataset, a common approach is to test a null hypothesis of statistical independence on all variable pairs using a non-parametric measure of dependence. However, because this approach attempts to identify…

Statistics Theory · Mathematics 2015-05-14 Yakir A. Reshef , David N. Reshef , Pardis C. Sabeti , Michael M. Mitzenmacher

The choice of admissible trading strategies in mathematical modelling of financial markets is a delicate issue, going back to Harrison and Kreps (1979). In the context of optimal portfolio selection with expected utility preferences this…

Computational Finance · Quantitative Finance 2017-07-25 Sara Biagini , Aleš Černý

We introduce a type and effect system, for an imperative object calculus, which infers "sharing" possibly introduced by the evaluation of an expression, represented as an equivalence relation among its free variables. This direct…

Programming Languages · Computer Science 2018-08-03 Paola Giannini , Tim Richter , Marco Servetto , Elena Zucca

We prove that the exponential distribution is the only one which satisfies a regression identity. This identity involves conditional expectation of the sample mean of record values given two record values outside of the sample.

Probability · Mathematics 2011-05-06 George P. Yanev

Prediction in a small-sized sample with a large number of covariates, the "small n, large p" problem, is challenging. This setting is encountered in multiple applications, such as precision medicine, where obtaining additional samples can…

Artificial Intelligence · Computer Science 2017-07-14 Pedram Daee , Tomi Peltola , Marta Soare , Samuel Kaski

Herein we define a measure of similarity between classification distributions that is both principled from the perspective of statistical pattern recognition and useful from the perspective of machine learning practitioners. In particular,…

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up…

Economics · Quantitative Finance 2017-07-18 Andrew J. Patton , Johanna F. Ziegel , Rui Chen

In performative prediction, predictions guide decision-making and hence can influence the distribution of future data. To date, work on performative prediction has focused on finding performatively stable models, which are the fixed points…

Machine Learning · Computer Science 2021-06-17 John Miller , Juan C. Perdomo , Tijana Zrnic

Forecasting is usually framed as a problem of model choice. This paper starts earlier, asking how much predictive information is available at each horizon. Under logarithmic loss, the answer is exact: the mutual information between the…

Applications · Statistics 2026-03-31 Peter Maurice Catt

In this paper we focus on the linear functionals defining an approximate version of the gradient of a function. These functionals are often used when dealing with optimization problems where the computation of the gradient of the objective…

Optimization and Control · Mathematics 2021-05-21 Marco Boresta , Tommaso Colombo , Alberto De Santis , Stefano Lucidi

A class of probability distributions is characterized via equalities in law between two order statistics shifted by independent exponential variables. An explicit formula for the quintile function of the identified family of distributions…

Probability · Mathematics 2011-07-26 M. Ahsanullah , V. B. Nevzorov , George P. Yanev

Dependency functions of dependent variables are relevant for i) performing uncertainty quantification and sensitivity analysis in presence of dependent variables and/or correlated variables, and ii) simulating random dependent variables. In…

Methodology · Statistics 2022-03-22 Matieyendou Lamboni