quantile regression

Quantile Regression is a statistical method aimed at estimating the relationship between the conditional quantiles of the dependent variable and the independent variables. Its objective is to provide a more comprehensive description of the data distribution, especially when dealing with asymmetric or heavy-tailed distributions, offering significant advantages. By minimizing weighted absolute deviations, Quantile Regression can effectively capture heterogeneous effects in the data, and it is widely applied in fields such as economics, finance, and medicine to evaluate risks and impacts at different quantile points.