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This paper takes into account the estimation for the two unknown parameters of the Chen distribution with bathtub-shape hazard rate function under the improved adaptive Type-II progressive censored data. Maximum likelihood estimation for…

Statistics Theory · Mathematics 2023-04-04 Li Zhang

We formulate a class of angular Gaussian distributions that allows different degrees of isotropy for directional random variables of arbitrary dimension. Through a series of novel reparameterization, this distribution family is indexed by…

Methodology · Statistics 2022-12-13 Zehao Yu , Xianzheng Huang

In a recent paper, Mazucheli et al. (2019) introduced the unit-Gompertz (UG) distribution and studied some of its properties. It is a continuous distribution with bounded support, and hence may be useful for modelling life-time phenomena.…

Statistics Theory · Mathematics 2020-06-12 M. Z. Anis , Debsurya De

Growth mixture models (GMMs) incorporate both conventional random effects growth modeling and latent trajectory classes as in finite mixture modeling; therefore, they offer a way to handle the unobserved heterogeneity between subjects in…

Methodology · Statistics 2017-11-15 Yuhong Wei , Yang Tang , Emilie Shireman , Paul D. McNicholas , Douglas L. Steinley

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

In this paper we investigate the flexibility of matrix distributions for the modeling of mortality. Starting from a simple Gompertz law, we show how the introduction of matrix-valued parameters via inhomogeneous phase-type distributions can…

Methodology · Statistics 2022-08-03 Hansjoerg Albrecher , Martin Bladt , Mogens Bladt , Jorge Yslas

In this paper, we introduce a new approach to generate flexible parametric families of distributions. These models arise on competitive and complementary risks scenario, in which the lifetime associated with a particular risk is not…

Applications · Statistics 2018-05-22 Pedro L. Ramos , Dipak K. Dey , Francisco Louzada , Victor H. Lachos

This paper introduces studies on exponentaited generalized Weibull Gompertz distribution EGWGD which generalizes a lot of distributions. Several properties of the EGWGD such as reversed (hazard) function, moments, maximum likelihood…

Statistics Theory · Mathematics 2015-01-14 M. A. EL-Damcese , Abdelfattah Mustafa , M. S. Eliwa

A survival model is derived from the exponential function using the concept of fractional differentiation. The hazard function of the proposed model generates various shapes of curves including increasing, increasing-constant-increasing,…

Statistics Theory · Mathematics 2007-06-13 Cheng K. Lee , Jenq-Daw Lee

Marshall and Olkin (1997, Biometrika, 84, 641 - 652) introduced a very powerful method to introduce an additional parameter to a class of continuous distribution functions and hence it brings more flexibility to the model. They have…

Methodology · Statistics 2018-02-20 Debasis Kundu , Vahid Nekoukhou

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

To improve nonparametric estimates of lifetime distributions, we propose using the increasing odds rate (IOR) model as an alternative to other popular, but more restrictive, ``adverse ageing'' models, such as the increasing hazard rate one.…

Methodology · Statistics 2022-12-13 Tommaso Lando , Idir Arab , Paulo Eduardo Oliveira

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

In this paper, we introduce a new class of bivariate distributions called the bivariate exponentiated extended Weibull distributions. The model introduced here is of Marshall-Olkin type. This new class of bivariate distributions contains…

Methodology · Statistics 2015-07-28 Rasool Roozegar , Ali Akbar Jafari

The two-parameter distribution known as exponential-Poisson (EP) distribution, which has decreasing failure rate, was introduced by Kus (2007). In this paper we generalize the EP distribution and show that the failure rate of the new…

Methodology · Statistics 2010-08-17 Wagner Barreto-Souza , Francisco Cribari-Neto

This article aims to introduced a new distribution named as extended xgamma (EXg) distribution. This generalization is derived from xgamma distribution (Xg), a special finite mixture of exponential and gamma distributions [see, Sen et al.…

Statistics Theory · Mathematics 2019-09-04 Mahendra Saha , Abhimanyu Singh Yadav , Arvind Pandey , Shivanshi Shukla , Sudhansu S Maiti

Due to its heavy-tailed and fully parametric form, the multivariate generalized Gaussian distribution (MGGD) has been receiving much attention for modeling extreme events in signal and image processing applications. Considering the…

Applications · Statistics 2017-02-27 F. Pascal , L. Bombrun , J. Y. Tourneret , Y. Berthoumieu

The peculiar properties of the Inverse Weibull (IW) distribution are shown. It is proven that the IW distribution is one of the few models having upside- down bathtub (UBT) shaped hazard function. Three real and typical de generative…

Methodology · Statistics 2013-05-30 Pasquale Erto

The Gompertz-Makeham distribution, which is used commonly to represent lifetimes based on laws of mortality, is one of the most popular choices for mortality modelling in the field of actuarial science. This paper investigates ordering…

Applications · Statistics 2019-12-10 Amarjit Kundu , Shovan Chowdhury , Narayanaswamy Balakrishnan

In this paper, we study the nonparametric maximum likelihood estimator (MLE) of a convex hazard function. We show that the MLE is consistent and converges at a local rate of $n^{2/5}$ at points $x_0$ where the true hazard function is…

Statistics Theory · Mathematics 2010-01-14 Hanna K. Jankowski , Jon A. Wellner