Risk management of supply chains in the digital transformation era: contribution and challenges of blockchain technology
K Rauniyar, X Wu, S Gupta, S Modgil… - … Management & Data …, 2023 - emerald.com
Purpose The high degree of likely disruption challenges organizations at all levels to
develop and implement innovative strategies. Ensuring supply chain continuity even during …
develop and implement innovative strategies. Ensuring supply chain continuity even during …
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 …
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 …
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 …
Birnbaum-Saunders quantile regression models with application to spatial data
In the present paper, a novel spatial quantile regression model based on the Birnbaum–
Saunders distribution is formulated. This distribution has been widely studied and applied in …
Saunders distribution is formulated. This distribution has been widely studied and applied in …
The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications
In this paper, we propose and derive a new regression model for response variables defined
on the open unit interval. By reparameterizing the unit generalized half-normal distribution …
on the open unit interval. By reparameterizing the unit generalized half-normal distribution …
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 …
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 …
A novel regression model for fractiles: Formulation, computational aspects, and applications to medical data
V Leiva, J Mazucheli, B Alves - Fractal and Fractional, 2023 - mdpi.com
Covariate-related response variables that are measured on the unit interval frequently arise
in diverse studies when index and proportion data are of interest. A regression on the mean …
in diverse studies when index and proportion data are of interest. A regression on the mean …
A new quantile regression model and its diagnostic analytics for a Weibull distributed response with applications
Standard regression models focus on the mean response based on covariates. Quantile
regression describes the quantile for a response conditioned to values of covariates. The …
regression describes the quantile for a response conditioned to values of covariates. The …