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A class of discrete probability distributions contains distributions with limited support. A typical example is some variant of a Likert scale, with response mapped to either the $\{1, 2, \ldots, 5\}$ or $\{-3, -2, \ldots, 2, 3\}$ set. An…

Applications · Statistics 2022-04-25 Bogdan Ćmiel , Jakub Nawała , Lucjan Janowski , Krzysztof Rusek

The generalized extreme value (GEV) distribution is commonly employed to help estimate the likelihood of extreme events in many geophysical and other application areas. The recently proposed blended generalized extreme value (bGEV)…

Applications · Statistics 2024-10-10 Nir Y. Krakauer

We approximate the distribution of the sum of independent but not necessarily identically distributed Bernoulli random variables using a shifted binomial distribution where the three parameters (the number of trials, the probability of…

Probability · Mathematics 2010-04-02 Vydas Čekanavičius , Erol A. Peköz , Adrian Röllin , Michael Shwartz

The exact expression is derived for the expected value, $< {p_i}> $, for the parameter for any bin $i$ of a histogram following a multinomial distribution derived by sorting $N$ observations into bins of $B$ classes, if $n_i$ of the…

Statistics Theory · Mathematics 2013-03-18 Jonathan M. Friedman

In this article, a generalized inverse xgamma distribution (GIXGD) has been introduced as the generalized version of the inverse xgamma distribution. The proposed model exhibits the pattern of non-monotone hazard rate and belongs to family…

Methodology · Statistics 2018-12-13 Harsh Tripathi , Abhimanyu Singh Yadav , Mahendra Saha , Sumit Kumar

Matrix variate beta (MVB) distributions are used in different fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. In this approach a unified methodology is proposed to…

Statistics Theory · Mathematics 2014-09-05 A. Bekker , M. Arashi

Binary classifiers trained on a certain proportion of positive items introduce a bias when applied to data sets with different proportions of positive items. Most solutions for dealing with this issue assume that some information on the…

Machine Learning · Statistics 2021-02-18 Marco J. H. Puts , Piet J. H. Daas

We develop a general method for computing logarithmic and log-gamma expectations of distributions. As a result, we derive series expansions and integral representations of the entropy for several fundamental distributions, including the…

Information Theory · Computer Science 2018-07-24 Mahdi Cheraghchi

In this paper we introduce five different algorithms based on method of moments, maximum likelihood and full Bayesian estimation for learning the parameters of the Inverse Gamma distribution. We also provide an expression for the KL…

Methodology · Statistics 2016-07-11 A. Llera , C. F. Beckmann

We propose a new modeling approach that is a generalization of generative and discriminative models. The core idea is to use an implicit parameterization of a joint probability distribution by specifying only the conditional distributions.…

Machine Learning · Computer Science 2016-12-06 Dmitrij Schlesinger , Carsten Rother

Through viewing out the literature, many generated distributions took a new special form of probability density function (PDF) in which it is written as a linear combination of n other distributions. Therefore, we define in this paper a new…

Statistics Theory · Mathematics 2022-11-15 Therar Kadri , Amina Halat

In this paper we propose an objective Bayesian estimation approach for the parameters of the generalized gamma distribution. Various reference priors are obtained, but showing that they lead to improper posterior distributions. We overcome…

Methodology · Statistics 2014-12-19 Pedro L. Ramos , Francisco Louzada

In this article, we proposed a new probability distribution named as power Maxwell distribution (PMaD). It is another extension of Maxwell distribution (MaD) which would lead more flexibility to analyze the data with non-monotone failure…

Applications · Statistics 2018-07-04 Abhimanyu Singh Yadav , Hassan S. Bakouch , Sanjay Kumar Singh , Umesh Singh

In extreme values theory, for a sufficiently large block size, the maxima distribution is approximated by the generalized extreme value (GEV) distribution. The GEV distribution is a family of continuous probability distributions, which has…

Methodology · Statistics 2021-09-28 Cira E. G. Otiniano , Bianca Sousa , Roberto Vila , Marcelo Bourguignon

Non-negative matrix factorization (NMF) is widely used as a feature extraction technique for matrices with non-negative entries, such as image data, purchase histories, and other types of count data. In NMF, a non-negative matrix is…

Computation · Statistics 2026-01-01 Ryo Ohashi , Hiroyasu Abe , Fumitake Sakaori

This paper proposes a generalized binomial distribution with four parameters, which is derived from the finite capacity queueing system with state-dependent service and arrival rates. This distribution is also generated from the conditional…

Statistics Theory · Mathematics 2016-10-18 Imoto Tomoaki , Ng Choung Min , Ong Seng Huat , Subrata Chakraborty

This paper introduces a cure rate survival model by assuming that the time to the event of interest follows a beta prime distribution and that the number of competing causes of the event of interest follows a negative binomial distribution.…

Methodology · Statistics 2018-12-20 Jeremias Leão , Marcelo Bourguignon , Manoel Santos-Neto , Helton Saulo

The negative binomial distribution (NBD) has been theorized to express a scale-invariant property of many-body systems and has been consistently shown to outperform other statistical models in both describing the multiplicity of…

High Energy Physics - Phenomenology · Physics 2023-10-09 S. V. Tezlaf

In this paper we propose a new four-parameters distribution with increasing, decreasing, bathtub-shaped and unimodal failure rate, called as the exponentiated Weibull-Poisson (EWP) distribution. The new distribution arises on a latent…

Methodology · Statistics 2012-12-24 Eisa Mahmoudi , Afsaneh Sepahdar

The Poisson-binomial distribution is useful in many applied problems in engineering, actuarial science, and data mining. The Poisson-binomial distribution models the distribution of the sum of independent but not identically distributed…

Computation · Statistics 2017-02-07 Man Zhang , Yili Hong , Narayanaswamy Balakrishnan
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