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In this paper we study bayesian analysis of Modified Weibull distribution under progressively censored competing risk model. This study is made for progressively censored data. We use deterministic scan Gibbs sampling combined with slice…

Computation · Statistics 2016-05-24 Arabin Kumar Dey , Abhilash Jha , Sanku Dey

We derive properties of Latent Variable Models for networks, a broad class of models that includes the widely-used Latent Position Models. These include the average degree distribution, clustering coefficient, average path length and degree…

Methodology · Statistics 2015-06-26 Riccardo Rastelli , Nial Friel , Adrian E. Raftery

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

The Sustainable Development Goals (SDGs) of the United Nations consist of 17 general objectives, subdivided into 169 targets to be achieved by 2030. Several SDG indices and indicators require continuous analysis and evaluation, and most of…

Methodology · Statistics 2025-08-26 João Inácio Scrimini , Cleber Bisognin , Renata Rojas Guerra , Fábio M. Bayer

In the present paper, the author discusses the derivation of unit distributions and the derivation of the generalized form using the order statistics. The author discusses the Kumaraswamy as the smallest order statistic of the unit power…

Methodology · Statistics 2025-09-17 Iman Mohamed Attia

Robust statistics traditionally focuses on outliers, or perturbations in total variation distance. However, a dataset could be corrupted in many other ways, such as systematic measurement errors and missing covariates. We generalize the…

Statistics Theory · Mathematics 2020-12-15 Banghua Zhu , Jiantao Jiao , Jacob Steinhardt

The projected normal distribution, also known as the angular Gaussian distribution, is obtained by dividing a multivariate normal random variable $\mathbf{x}$ by its norm $\sqrt{\mathbf{x}^T \mathbf{x}}$. The resulting random variable…

Methodology · Statistics 2025-06-24 Daniel Herrera-Esposito , Johannes Burge

There is a difficulty in finding an estimate of variance of the profile likelihood estimator in the joint model of longitudinal and survival data. We solve the difficulty by introducing the ``statistical generalized derivative''. The…

Statistics Theory · Mathematics 2018-07-23 Yuichi Hirose , Ivy Liu

A new distribution named intensive natural distribution is introduced with the intent of consolidating statistics and empirical data. Based on the probability derived from the Bernoulli distribution, this method extended also Poisson…

Statistics Theory · Mathematics 2011-05-05 Alessandro Felluga , Stefano Tiziani

In branching process theory, linear-fractional distributions are commonly used to model individual reproduction, especially when the goal is to obtain more explicit formulas than those derived under general model assumptions. In this…

Probability · Mathematics 2025-04-07 Gerold Alsmeyer , Viet Hung Hoang

Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parameter estimation remains challenging in these three…

Methodology · Statistics 2024-10-16 Sarah S. Ji , Benjamin B. Chu , Hua Zhou , Kenneth Lange

Many generalised distributions exist for modelling data with vastly diverse characteristics. However, very few of these generalisations of the normal distribution have shape parameters with clear roles that determine, for instance, skewness…

Methodology · Statistics 2023-12-01 Andriette Bekker , Matthias Wagener , Muhammad Arashi

By discussing several examples, the theory of generalized functional models is shown to be very natural for modeling some situations of reasoning under uncertainty. A generalized functional model is a pair (f, P) where f is a function…

Artificial Intelligence · Computer Science 2013-02-08 Paul-Andre Monney

A new 2 parameter unit Weibull distribution is defined on the unit interval (0,1). The methodology of deducing its PDF, some of its properties and related functions are discussed. The paper is supplied by many figures illustrating the new…

Methodology · Statistics 2025-02-17 Iman Mohammed Attia

Optimization is widely used in statistics, and often efficiently delivers point estimates on useful spaces involving structural constraints or combinatorial structure. To quantify uncertainty, Gibbs posterior exponentiates the negative loss…

Methodology · Statistics 2025-07-23 Cheng Zeng , Eleni Dilma , Jason Xu , Leo L Duan

Let $\{X_{n}, n\ge 1\}$ be a sequence of independent random variables with common general error distribution $GED(v)$ with shape parameter $v>0$, and let $M_{n,r}$ denote the $r$th largest order statistics of $X_{1}, X_{2}, \cdots, X_{n}$.…

Probability · Mathematics 2019-05-07 Yingyin Lu , Zuoxiang Peng

In a recent paper in this journal [J. Stat. Mech. (2009) P02037] we proposed a new, physically motivated, distribution function for modeling individual incomes having its roots in the framework of the k-generalized statistical mechanics.…

General Finance · Quantitative Finance 2012-12-07 F. Clementi , M. Gallegati , G. Kaniadakis

The paper presents improved mathematical models and methods for statistical regularities in the behavior of some important characteristics of precipitation: duration of a wet period, maximum daily and total precipitation volumes within a…

Statistics Theory · Mathematics 2019-02-01 Victor Korolev , Andrey Gorshenin

This paper proposes the k-generalized distribution as a model for describing the distribution and dispersion of income within a population. Formulas for the shape, moments and standard tools for inequality measurement - such as the Lorenz…

General Finance · Quantitative Finance 2009-01-31 F. Clementi , T. Di Matteo , M. Gallegati , G. Kaniadakis

The Lindley distribution and its numerous generalizations are widely used in statistical and engineering practice. Recently, a power transformation of Lindley distribution, called the power Lindley distribution, has been introduced by M. E.…

Statistics Theory · Mathematics 2019-07-02 Mohammed Khalleefah , Sofiya Ostrovska , Mehmet Turan
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