Quantile Estimation Using the Log-Skew-Normal Linear Regression Model with Application to Children’s Weight Data

In this article, we establish properties that relate quantiles of the log-skew-normal distribution to its parameters, allowing us investigate relationship between a positive skewed response variable and set explanatory variables via linear regression model. We compute maximum likelihood estimates parameters through correspondence skew-normal models. Monte Carlo simulations show satisfactory performance quantile estimators. An application children’s data is presented discussed.