An overview on parametric quantile regression models and their computational implementation with applications to biomedical problems including COVID-19 data
Quantile regression allows us to estimate the relationship between covariates and any
quantile of the response variable rather than the mean. Recently, several statistical …
quantile of the response variable rather than the mean. Recently, several statistical …
Modeling COVID-19 cases statistically and evaluating their effect on the economy of countries
COVID-19 infections have plagued the world and led to deaths with a heavy pneumonia
manifestation. The main objective of this investigation is to evaluate the performance of …
manifestation. The main objective of this investigation is to evaluate the performance of …
On the arcsecant hyperbolic normal distribution. Properties, quantile regression modeling and applications
This work proposes a new distribution defined on the unit interval. It is obtained by a novel
transformation of a normal random variable involving the hyperbolic secant function and its …
transformation of a normal random variable involving the hyperbolic secant function and its …
A new quantile regression for modeling bounded data under a unit Birnbaum–Saunders distribution with applications in medicine and politics
Quantile regression provides a framework for modeling the relationship between a response
variable and covariates using the quantile function. This work proposes a regression model …
variable and covariates using the quantile function. This work proposes a regression model …
An Overview of Kriging and Cokriging Predictors for Functional Random Fields
This article presents an overview of methodologies for spatial prediction of functional data,
focusing on both stationary and non-stationary conditions. A significant aspect of the …
focusing on both stationary and non-stationary conditions. A significant aspect of the …
Breakpoint analysis for the COVID-19 pandemic and its effect on the stock markets
In this research, statistical models are formulated to study the effect of the health crisis
arising from COVID-19 in global markets. Breakpoints in the price series of stock indexes are …
arising from COVID-19 in global markets. Breakpoints in the price series of stock indexes are …
Log‐symmetric quantile regression models
Regression models based on the log‐symmetric family of distributions are particularly useful
when the response variable is continuous, positive, and asymmetrically distributed. In this …
when the response variable is continuous, positive, and asymmetrically distributed. In this …
Cokriging prediction using as secondary variable a functional random field with application in environmental pollution
Cokriging is a geostatistical technique that is used for spatial prediction when realizations of
a random field are available. If a secondary variable is cross-correlated with the primary …
a random field are available. If a secondary variable is cross-correlated with the primary …
Sign, Wilcoxon and Mann-Whitney tests for functional data: An approach based on random projections
Sign, Wilcoxon and Mann-Whitney tests are nonparametric methods in one or two-sample
problems. The nonparametric methods are alternatives used for testing hypothesis when the …
problems. The nonparametric methods are alternatives used for testing hypothesis when the …
Vasicek quantile and mean regression models for bounded data: New formulation, mathematical derivations, and numerical applications
The Vasicek distribution is a two-parameter probability model with bounded support on the
open unit interval. This distribution allows for different and flexible shapes and plays an …
open unit interval. This distribution allows for different and flexible shapes and plays an …