# Questions tagged [quantile-regression]

Quantile regression allows us to estimate the effect of a set of predictor variables over the entire distribution of the outcome variable or any particular quantile.

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### Combining information from different quantiles

I have a number of "mostly" Gaussian distributions (in truth a Gauss core and longer tails). I am interested in the width of this distributions. Given that I do not know the amount of tails ...
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### Obtaining z-scores for coefficients of quantile regression with sampling weights applied in R

I would need to obtain z-scores for coefficients of quantile regression with sampling weights applied in R to be able to compare results from different datasets. Can I just compute them as "z-...
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### Quantile regression with sampling weights in R

I am trying to implement quantile regression with sampling weights in R for my analysis. I know in lm() and glm() in R, standard ...
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### Median regression

I am trying to understand the reason I'm having different results estimating median values with R median and rq (quantreg) ...
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### Implementing Quantile Loss function

I have been reading about Quantile Regression and the Quantile Loss function, but I have to admit I am a bit lost as how to practically implement it. I would like to use it to calculate the prediction ...
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### What does it mean to have symmetric quantiles?

I'm using quantile regression for my paper, and my results are symmetric i don't understand what that means. Please explain the symmetry of quantiles and how does this effect the results and how to ...
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### Estimating quantiles using quantile regression

I understand that quantile regression estimates the conditional quantile of some measured variable (call the variable $y$), but can you use quantile regression to estimate an unconditional quantile of ...
1 vote
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### Quantile regression and sample size for a given tau

I am performing the quantile regression in R on a non linear model (that is done by using nlrq). I am getting the coefficients for the desired quantiles (tau = 0.05, 0.50, 0.95). All very nice, but ...
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### For What Kinds Of Problems is Quantile Regression Useful?

I am trying to learn more about Quantile Regression. As I understand, Quantile Regression is used to estimate the conditional quantile of a response variable (given predictor variables). ...
115 views

### Use linear mixed model or linear quantile mixed model for non-normal residuals?

I started with this initial model: m1 <- lmer(response ~ treatment + (1|subjectID), data = data) However, the residuals of the model are heavy-tailed (presumably enough to violate the normality ...
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