We propose a new family of error distributions for model-based quantile regression, which is constructed through a structured mixture of normal distributions. The construction enables fixing specific percentiles of the distribution while, at the same time, allowing for varying mode, skewness and tail behavior. It thus overcomes the severe limitation of the asymmetric Laplace distribution – the ...

background: low birth weight is one of the key indicators to assess the health of infants, and appropriate birth weight is one of the most important goals of any health system which also reflects the quality of prenatal care. objectives: the present research aimed to study some of the factors associated with low birth weight using quantile regression analysis. methods: a cross-sectional study w...

Quantile regression is a statistical technique intended to estimate, and conduct inference about the conditional quantile functions. Just as the classical linear regression methods estimate models for conditional mean function, quantile regression offers a mechanism for estimating models for conditional median function, and the full range of other conditional quantile functions. In this paper d...