QuantReg from statsmodels package in Python gives very different results than in R, using the data as shown in the following code. I tried the STACKLOSS data in Python and R respectively, and the ...

I used the quantreg package in R to compute the quantile regression model. In the model, dependent Variable(Y) is NAS_DELAY, and the independent variable(Xs) are SEANSON1TO4, SEANSON2TO4, SEANSON3T...

When I run a quantile regression in R, using the quantreg package, and then I run summary(quantregObject), I get this error message: Error in base::backsolve(r, x, k = k, upper.tri = upper.tri, ...

I would like to get 95% confidence intervals for the regression coefficients of a quantile regression. You can calculate quantile regressions using the rq function of the quantreg package in R (com...

I am running quantile regressions for several independent variables separately (same dependent). I want to plot only the slope estimates over several quantiles of each variable in a single plot. ...

Say I have a data frame like this: X <- data_frame( x = rep(seq(from = 1, to = 10, by = 1), 3), y = 2*x + rnorm(length(x), sd = 0.5), g = rep(LETTERS[1:3], each = length(x)/3)) How can I f...

I am using the quantreg package to run the following quantile regression in R: bank <-rq(gekX~laggekVIXclose+laggekliquidityspread+lagdiffthreeMTBILL+ lagdiffslopeyieldcurve+lagdiffcreditspread...

Using R, and package quantreg, I am performing quantile regression analyses to my data. I can get access to the p-values using the se (standard error) estimator in the summary function, as below, ...