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In a multiple testing context, we consider a semiparametric mixture model with two components where one component is known and corresponds to the distribution of $p$-values under the null hypothesis and the other component $f$ is…

Applications · Statistics 2013-04-04 Van Hanh Nguyen , Catherine Matias

This paper defines a new class of fractional differential operators alongside a family of random variables whose density functions solve fractional differential equations equipped with these operators. These equations can be further used to…

Probability · Mathematics 2019-05-28 Corina D. Constantinescu , Jorge M. Ramirez , Wei R. Zhu

Multivariate normal mixtures provide a flexible model for high-dimensional data. They are widely used in statistical genetics, statistical finance, and other disciplines. Due to the unboundedness of the likelihood function, classical…

Statistics Theory · Mathematics 2008-05-27 Jiahua Chen , Xianming Tan

In numerous instances, the generalized exponential distribution can be used as an alternative to the most widely used non-regular family of distributions: Weibull, gamma, lognormal with three-parameters when analyzing lifetime or any skewed…

Methodology · Statistics 2026-03-03 Kiran Prajapat , Sharmishtha Mitra , Debasis Kundu

Hazard ratios are prone to selection bias, compromising their use as causal estimands. On the other hand, the hazard difference has been shown to remain unaffected by the selection of frailty factors over time. Therefore, observed hazard…

Statistics Theory · Mathematics 2022-11-01 Richard Post , Edwin van den Heuvel , Hein Putter

Motivated by the need to analyze continuously updated data sets in the context of time-to-event modeling, we propose a novel nonparametric approach to estimate the conditional hazard function given a set of continuous and discrete…

Methodology · Statistics 2025-07-03 Daphné Aurouet , Valentin Patilea

In this paper introduces a new family of continuous distributions namely the Poison transmuted-G family of distribution is proposed by inducing two addition parameter on the base line G distribution. Some of its mathematical properties…

Statistics Theory · Mathematics 2020-05-12 Laba Handique , Subrata Chakraborty

In this article, a general family of bivariate distributions is used to model competing risks data with dependent factors. The general structure of competing risks data considered here includes ties. A comprehensive inferential framework…

Methodology · Statistics 2022-06-22 Aakash Agrawal , Ayon Ganguly , Debanjan Mitra

Survival models capture the relationship between an accumulating hazard and the occurrence of a singular event stimulated by that accumulation. When the model for the hazard is sufficiently flexible survival models can accommodate a wide…

Methodology · Statistics 2024-03-04 Michael Betancourt

Several formulations have long existed in the literature in the form of continuous mixtures of normal variables where a mixing variable operates on the mean or on the variance or on both the mean and the variance of a multivariate normal…

Probability · Mathematics 2020-03-31 Reinaldo B. Arellano-Valle , Adelchi Azzalini

Survivorship analysis allows to statistically analyze situations that can be modeled as waiting times to an event. These waiting times are characterized by the cumulative hazard rate, which can be estimated by the Nelson-Aalen estimator or…

Statistics Theory · Mathematics 2019-07-04 Niklas Hohmann

The relative ageing is an important notion which is useful to measure how a system ages relative to another one. Among all existing stochastic orders, there are two important orders describing the relative ageing of two systems, namely,…

Applications · Statistics 2019-06-25 Nil Kamal Hazra , Neeraj Misra

In this paper, a new mixture family of multivariate normal distributions, formed by mixing multivariate normal distribution and skewed distribution, is constructed. Some properties of this family, such as characteristic function, moment…

Methodology · Statistics 2020-09-24 Me'raj Abdi , Mohsen Madadi , N. Balakrishnan , Ahad Jamalizadeh

We propose a method to infer causal structures containing both discrete and continuous variables. The idea is to select causal hypotheses for which the conditional density of every variable, given its causes, becomes smooth. We define a…

Machine Learning · Statistics 2009-10-30 Dominik Janzing , Xiaohai Sun , Bernhard Schoelkopf

Count data are omnipresent in many applied fields, often with overdispersion due to an excess of zeroes or extreme values. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we focus here on the…

Statistics Theory · Mathematics 2022-04-25 Samuel Valiquette , Frédéric Mortier , Jean Peyhardi , Gwladys Toulemonde

Evaluating the causal health effects of multivariate, continuous exposures, such as air pollution mixtures, is a critical public health challenge. A primary obstacle is the frequent violation of the positivity assumption, which renders the…

Methodology · Statistics 2026-05-05 Zhuochao Huang , Kejin Dong , Tuo Lin , Joseph Antonelli

Understanding under what conditions populations, whether they be plants, animals, or viral particles, persist is an issue of theoretical and practical importance in population biology. Both biotic interactions and environmental fluctuations…

Dynamical Systems · Mathematics 2015-12-16 Sebastian J. Schreiber

Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of…

Physics and Society · Physics 2024-01-02 Changwang Zhang , Shi Zhou , Joel C. Miller , Ingemar J. Cox , Benjamin M. Chain

The need for improved functionalities is driving the search for more complicated multi-component materials. Despite the factorially increasing composition space, ordered compounds with 4 or more species are rare. Here, we unveil the…

Materials Science · Physics 2019-06-05 Cormac Toher , Corey Oses , David Hicks , Stefano Curtarolo

Mixtures of generalized normal distributions (MGND) have gained popularity for modelling datasets with complex statistical behaviours. However, the estimation of the shape parameter within the maximum likelihood framework is quite complex,…

Methodology · Statistics 2025-06-03 Pierdomenico Duttilo , Stefano Antonio Gattone
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