In this paper, we propose a new distribution with unitary support which can be characterized as ratio of the type $W=X_1/(X_1+X_2)$, where $(X_1, X_2)^\top$ follows bivariate extreme Fr\'echet margins, that is, $X_1$ and $X_2$ are two correlated random variables. Some mathematical properties such identifiability, symmetry, stochastic representation, characterization ratio, moments, stress-strength probability, quantiles, maximum likelihood method rigorously analyzed. Two applications discussed.

Grain producers in Brazil often depend on third-party services for the transportation, processing and storage of their production, as, most part, they do not have silos properties. In this context, efficient logistics is essential to optimize processes increase reliability between customers service providers. This study focuses logistical analysis truck traffic at two grain plants, examining different receiving protocols evaluate internal vehicle flow during peak production conditions. The...

Abstract The Birnbaum–Saunders (BS) distribution is a model that frequently appears in the statistical literature and has proved to be very versatile efficient across wide range of applications. However, despite growing interest study this development many articles, few them have considered data with dependency structure. To fill gap, we introduce new class time series models based on BS distribution, which allows modeling positive asymmetric an autoregressive We call these moving average...

Income modeling is crucial in determining workers’ earnings and an important research topic labor economics. Traditional regressions based on normal distributions are statistical models widely applied. However, income data have asymmetric behavior best modeled by non-normal distributions. The objective of this work to propose parametric quantile two distributions: Dagum Singh–Maddala. proposed regression reparameterizations the original inserting a parameter. We present reparameterizations,...

The Gumbel model is a very popular statistical due to its wide applicability for instance in the course of certain survival, environmental, financial or reliability studies. In this work, we have introduced bimodal generalization distribution thatcan be an alternative data. We derive analytical shapes corresponding probability density function and thehazard rate provide graphical illustrations. Furthermore, discussed properties such as mode, bimodality, moment generating moments. Our results...

Modelling is challenging topic and using parametric models important stage to reach flexible function for modelling. Weibull distribution has shape scale parameters which play the main role Bimodality parameter added so bimodal can capture real data set with bimodality be actually combination of two populations. The properties proposed estimation method are examined extensively show its usability in modelling accurately safely practitioners. After examination as first issue, it appropriate...

We define a new quantile regression model based on reparameterized exponentiated odd log-logistic Weibull distribution, and obtain some of its structural properties. It includes as sub-models known models that can be utilized in many areas. The maximum likelihood method is adopted to estimate the parameters, several simulations are performed study finite sample properties estimators. applicability proposed well justified by means gastric carcinoma dataset.

In this paper, we discuss some theoretical results and properties of the discrete Weibull distribution, which was introduced by Nakagawa Osaki [The distribution. IEEE Trans Reliab. 1975;24:300–301]. We study monotonicity probability mass, survival hazard functions. Moreover, reliability, moments, p-quantiles, entropies order statistics are also studied. consider likelihood-based methods to estimate model parameters based on complete censored samples, derive confidence intervals. two...

In this paper, we propose a bimodal gamma distribution using quadratic transformation based on the alpha-skew-normal model. We discuss several properties of such as mean, variance, moments, hazard rate and entropy measures. Further, new regression model with censored data distribution. This can be very useful to analysis real could give more realistic fits than other special models. Monte Carlo simulations were performed check bias in maximum likelihood estimation. The proposed models are...

The modality is an important topic for modelling. Using parametric models efficient way when real data set shows trimodality. In this paper, we propose a new class of trimodal probability distributions, that is, distributions have up to three modes. Trimodality itself achieved by applying proper transformation density function certain continuous distributions. At first, obtain preliminary results arbitrary g(x) and, next, focus on the Gaussian case, studying model more deeply. distribution...

We construct a new partially linear regression based on reparametrized generalized gamma distribution with two systematic components that can be easily interpreted. Its parameters are estimated by penalized maximum likelihood. For different parameter settings, sample sizes, and censoring percentages, some simulations performed to examine the accuracy of likelihood estimators, empirical residuals compared standard normal distribution. The methodology is applied breast cancer data in city João...

In this article, using inverse integral transforms, we derive the exact distribution of random variable X that is involved in ratio Z=dX/(X+Y) where and Y are independent variables having same support, Z have known distributions. We introduce new distributions way. As an application obtained results, several examples presented.

ABSTRACT In this paper, we propose and investigate closed‐form point estimators for a weighted exponential family. We also develop bias‐reduced version of these proposed through bootstrap methods. Estimators are assessed using Monte Carlo simulation, revealing favourable results the estimators. illustrate methodology with use two real data sets.

This paper introduces bivariate log-symmetric models for analyzing the relationship between two variables, assuming a family of distributions. These offer greater flexibility than lognormal distribution, allowing better representation diverse distribution shapes and behaviors in data. The is widely used various scientific fields includes distributions such as log-normal, log-Student-t, log-Laplace, among others, providing several options modeling different data types. However, there are few...

This work aims to study the factors that increase risk of death hospitalized patients diagnosed with COVID-19 through odd log-logistic regression model for censored data two systematic components, as well provide new mathematical properties this distribution. To achieve this, a dataset individuals residing in city Campinas (Brazil) was used and simulations were performed investigate accuracy maximum likelihood estimators proposed model. The provided properties, such stochastic...

We define a four-parameter extended Rayleigh distribution which is quite flexible model to analyze positive data, and includes as special models the odd log-logistic generalized Rayleigh, exponentiated distributions.We obtain linear representation some of its mathematical properties.We construct regression from new with two systematic components for censored data.The estimation done by maximum likelihood.The utility proved in real applications.

We use the Clayton and Frank copulas exponentiated odd log-logistic family to define a new flexible bivariate model fit bimodal asymmetry data. The allow different distributions for response variable, thus making analysis more suitable. present some structural properties of describe simulation study show consistency estimators. construct regression based on oak lettuce plant data concentrations silicon dioxide organosilicon compounds. check variables fresh weight height together in order...