Abstrato

An Application of Box-Cox Transformation in Quantile Regression

Sejuti Haque1*, Md. Rezaul Karim

This paper studies the real data application of Box-Cox transformation in Quantile regression. Box-Cox transformation for quantile regression is implemented to estimate quantiles by estimating parameters. For illustration purposes, an actual data application is included that shows the percentage of daily SARS-Cov-2 infected people tested for COVID-19 infection and climatic variables like temperature and humidity. We discovered that temperature and humidity have a substantial impact on the number of daily SARS-Cov-2-infected individuals screened for COVID-19 infection.