I need the description of Huber sandwich estimate method for Quantile regression and it is urgent:) please help!

I found this "a Huber sandwich estimate using a local estimate of the sparsity function." Sparsity function looks like that $s(\theta)=f(F^{-1}(\theta))^{-1}$, $F$ is a distribution of residuals and $f$ is a density function of $F$. So my question is what exactly means "local estimate of sparsity function":)

I need the description of Huber sandwich estimate method for quantile regression.

I found this "a Huber sandwich estimate using a local estimate of the sparsity function". Sparsity function looks like $s(\theta)=f(F^{-1}(\theta))^{-1}$, $F$ is a distribution of residuals and $f$ is a density function of $F$. So my question is what exactly means "local estimate of sparsity function":)

I need the description of Huber sandwich estimate method for Quantile regression and it is urgent:) please help!

I need the description of Huber sandwich estimate method for Quantile regression and it is urgent:) please help!

I found this "a Huber sandwich estimate using a local estimate of the sparsity function." Sparsity function looks like that $s(\theta)=f(F^{-1}(\theta))^{-1}$, $F$ is a distribution of residuals and $f$ is a density function of $F$. So my question is what exactly means "local estimate of sparsity function":)