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This paper designs a statistical quantification towards the intermittent power uncertainty in power systems. A negative-exponential forecast uncertainty function is constructed to represent the relationship between the statistics of…

Systems and Control · Computer Science 2017-07-13 Zongjie Wang , Zhizhong Guo

Sufficient conditions for comparing the convolutions of heterogeneous gamma random variables in terms of the usual stochastic order are established. Such comparisons are characterized by the Schur convexity properties of the cumulative…

Probability · Mathematics 2016-01-20 Farbod Roosta-Khorasani , Gabor J. Szekely

In mortality modelling, cohort effects are often taken into consideration as they add insights about variations in mortality across different generations. Statistically speaking, models such as the Renshaw-Haberman model may provide a…

Methodology · Statistics 2024-08-01 Yiping Guo , Johnny Siu-Hang Li

Age-specific life-table death counts observed over time are examples of densities. Non-negativity and summability are constraints that sometimes require modifications of standard linear statistical methods. The centered log-ratio…

Methodology · Statistics 2025-10-28 Han Lin Shang , Steven Haberman

A new four-parameter model called the Marshall-Olkin extended generalized Gompertz distribution is introduced. Its hazard rate function can be constant, increasing, decreasing, upside-down bathtub or bathtub-shaped depending on its…

Statistics Theory · Mathematics 2019-04-23 Lazhar Benkhelifa

Let K be a random variable following a truncated exponential distribution. Such distributions are described by a single parameter here denoted by $\gamma$. The determination of $\gamma$ by Maximum Likelihood methods leads to a…

Probability · Mathematics 2015-01-13 Grant Keady

Lifespan distributions of populations of quite diverse species such as humans and yeast seem to surprisingly well follow the same empirical Gompertz-Makeham law, which basically predicts an exponential increase of mortality rate with age.…

Quantitative Methods · Quantitative Biology 2011-10-18 André Grüning , Aasis Vinayak PG

Multivariate generalized Gamma convolutions are distributions defined by a convolutional semi-parametric structure. Their flexible dependence structures, the marginal possibilities and their useful convolutional expression make them…

Statistics Theory · Mathematics 2022-03-28 Oskar Laverny

Probabilistic operational semantics for a nondeterministic extension of pure lambda calculus is studied. In this semantics, a term evaluates to a (finite or infinite) distribution of values. Small-step and big-step semantics are both…

Logic in Computer Science · Computer Science 2011-06-28 Ugo Dal Lago , Margherita Zorzi

Beta coefficients for linear regression models represent the ideal form of an interpretable feature effect. However, for non-linear models and especially generalized linear models, the estimated coefficients cannot be interpreted as a…

Machine Learning · Computer Science 2022-01-24 Christian A. Scholbeck , Giuseppe Casalicchio , Christoph Molnar , Bernd Bischl , Christian Heumann

The statistical properties of the multivariate Gamma-Gamma ($\Gamma \Gamma$) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (PDF),…

Information Theory · Computer Science 2016-11-18 Jiayi Zhang , Michail Matthaiou , George K. Karagiannidis , Linglong Dai

A GGC (Generalized Gamma Convolution) representation of Riemann's Xi-function is constructed.

General Mathematics · Mathematics 2018-10-16 Nicholas G. Polson

In the aftermath of the COVID-19 pandemic, empirical data have revealed that large-scale health crises not only cause immediate disruptions in mortality dynamics but also have persistent effects that may last for several years. Existing…

Applications · Statistics 2026-03-26 Yanxin Liu , Kenneth Q. Zhou

The computation and inversion of the binomial and negative binomial cumulative distribution functions play a key role in many applications. In this paper, we explain how methods used for the central beta distribution function (described in…

Classical Analysis and ODEs · Mathematics 2020-01-14 A. Gil , J. Segura , N. M. Temme

We address the statistical estimation of composite functionals which may be nonlinear in the probability measure. Our study is motivated by the need to estimate coherent measures of risk, which become increasingly popular in finance,…

Statistics Theory · Mathematics 2015-04-13 Darinka Dentcheva , Spiridon Penev , Andrzej Ruszczynski

What is aging? Mechanistic answers to this question remain elusive despite decades of research. Here, we propose a mathematical model of cellular aging based on a model gene interaction network. Our network model is made of only non-aging…

Molecular Networks · Quantitative Biology 2023-09-12 Hong Qin

First derivatives of the Whittaker function $\mathrm{M}_{\kappa ,\mu }\left(x\right) $ with respect to the parameters are calculated. Using the confluent hypergeometric function, these derivarives can be expressed as infinite sums of…

Classical Analysis and ODEs · Mathematics 2023-04-28 Alexander Apelblat , Juan Luis González-Santander

Linear Quadratic Gaussian (LQG) systems are well-understood and methods to minimize the expected cost are readily available. Less is known about the statistical properties of the resulting cost function. The contribution of this paper is a…

Systems and Control · Computer Science 2016-02-09 Hildo Bijl , Jan Willem van Wingerden , Thomas B. Schön , Michel Verhaegen

In this article, we present a new two-dimensional generalization of the gamma function based on the product of the one-dimensional generalized beta function and the one-dimensional generalized gamma function. As will become clear later,…

General Mathematics · Mathematics 2024-03-18 Artem M. Ponomarenko

In this paper, we introduce a new and efficient data augmentation approach to the posterior inference of the models with shape parameters when the reciprocal gamma function appears in full conditional densities. Our approach is to…

Methodology · Statistics 2023-11-08 Yasuyuki Hamura , Kaoru Irie , Shonosuke Sugasawa
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