r R-squared in quantile regression

I am using quantile regression to find predictors of 90th percentile of my data. I am doing this in R using the quantreg package. How can I determine $r^2$ for quantile regression which will indicate how much of variability is being explained by predictor variables?

What I really want to know: "Any method I can use to find how much of variability is being explained? "". Significance levels by P values is available in output of command: summary(rq(formula,tau,data)). How can I get goodness of fit?

Thanks for your help.

r-squared in quantile regression

I am using quantile regression to find predictors of 90th percentile of my data. I am doing this in R using the quantreg package. How can I determine $r^2$ for quantile regression which will indicate how much of variability is being explained by predictor variables?

What I really want to know: "Any method I can use to find how much of variability is being explained? ". Significance levels by P values is available in output of command: summary(rq(formula,tau,data)). How can I get goodness of fit?

Thanks for your help.

R-squared in quantile regression

I am using quantile regression to find predictors of 90th percentile of my data. I am doing this in R using the quantreg package. How can I determine $r^2$ for quantile regression which will indicate how much of variability is being explained by predictor variables?

What I really want to know: "Any method I can use to find how much of variability is being explained?". Significance levels by P values is available in output of command: summary(rq(formula,tau,data)). How can I get goodness of fit?