The zero-adjusted log-symmetric quantile regression model applied to extramarital affairs data

05/09/2021
by   Danúbia R. Cunha, et al.
0

In this work, we propose a zero-adjusted log-symmetric quantile regression model. Initially, we introduce zero-adjusted log-symmetric distributions, which allow for the accommodation of zeros. The estimation of the parameters is approached by the maximum likelihood method and a Monte Carlo simulation is performed to evaluate the estimates. Finally, we illustrate the proposed methodology with the use of a real extramarital affairs data set.

READ FULL TEXT

page 9

page 12

research
03/07/2021

On a log-symmetric quantile tobit model applied to female labor supply data

The classic censored regression model (tobit model) has been widely used...
research
12/18/2018

A residual for outlier identification in zero adjusted regression models

Zero adjusted regression models are used to fit variables that are discr...
research
12/19/2020

On a length-biased Birnbaum-Saunders regression model applied to meteorological data

The length-biased Birnbaum-Saunders distribution is both useful and prac...
research
02/01/2018

Zero-adjusted Birnbaum-Saunders regression model

In this paper we introduce the zero-adjusted Birnbaum-Saunders regressio...
research
02/08/2021

A Bayesian Hurdle Quantile Regression Model for Citation Analysis with Mass Points at Lower Values

Quantile regression presents a complete picture of the effects on the lo...
research
05/03/2022

An R Package AZIAD for Analyzing Zero-Inflated and Zero-Altered Data

Sparse data with a large portion of zeros arise in many scientific disci...
research
09/20/2020

Skewed probit regression – Identifiability, contraction and reformulation

Skewed probit regression is but one example of a statistical model that ...

Please sign up or login with your details

Forgot password? Click here to reset