# 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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### Quantile regression model when most values are 0- data cleaning or different quantile?

I asked a question on performing quantile regression on a specific dataset and set of variables (which is unanswered as of now- maybe the question isn't as clear.) The following question is somewhat ...
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### Quantile regression: getting 0 intercept and coefficients

I have three variables- two independent x1, x2 and one response y1. Scatterplot for the data is, as follows. I want to perform ...
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### Generalized quantile regression? Transforming a conditional quantile like we transform conditional expected value

Linear models are models like $\mathbb E\left[Y\vert X\right]=X\beta$. Linear quantile regression models replace $\mathbb E\left[Y\vert X\right]$ with $Q_{\tau}\left(Y\vert X\right)$ for conditional ...
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### A Quantile Analysis of the predictive power of the Value factor

Value factor is implemented using three different measures: a. EPQ is the E/P where E is last quarter EPS b. EP12 is the E/P where E is the last 12 months EPS c. BTM is the book to market ratio I need ...
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### Which regression models are appropriate for (ratios of) two different but dependent counts?

Consider a variable Y which is the ratio of the frequencies of two words/concepty (f,g) in a text: Y = f/g. Since the texts do not have equal length, the denominator when calculating the percentage of ...
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### Can a Variable Be Both Dependent and Independent?

We can see that the GDP growth, represented by "y" is the dependent variable and independent variable. I would like to perform quantile regression in Eviews, with ...
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### Scikit-learn QuantileRegressor memory allocation error. No issue with statsmodel QuantReg with the same data

I'm trying to fit a quantile regression model to my input data. I would like to use sklearn, but I am getting a memory allocation error when I try to fit the model. The same data with the statsmodels ...
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### What is the meaning of a quantile regression model that predicts the conditional mean?

What does that phrase "quantile regression model that predicts the conditional mean" mean? How to interpret that? I found it in Liu et al. (2020). The authors have compared the results of ...
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### Which metric to use to evaluate Quantile Regression?

I have a prediction problem for which I want to predict the 75% Quantile using Quantile Regression. I am a little bit confused on how to evaluate this model (and also compare different models). If I ...
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### Dependent value largely right skewed. What are my options?

I am modeling a dependent variable which is heavily right skewed by a large number of independant variables. This variable is integer. But let's assume this is our model. $Y = a_0 X_0 + a_1 X_1 + b_0$...
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### Using an independent variable correlated with the residuals in quantile regression

If an independent variable correlates with the residuals in quantile regression, does it produce biased coefficient estimates? In ordinary least squares regression, if the independent variable is ...
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### Time fixed effect - calculate the net of time effect

I have a data that includes two categories, one being Manchester and another Leeds. This is panel data. I have a Year variable, a dummy for city 0 (Man) 1 (Leeds) and a dummy for each Year. How would ...
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### n-th quantile for bivariate variable

I generate a 2000 bivariate random samples which are negative correlated. I used np.quantile to generate 10 quantile from this random samples. The related point is marked in the following figure. I am ...
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### Theory understanding behind quantile regression

As part of my studies in ecology, I am trying to reproduce a quantile regression method described in Karlsson et. al (2022) (source: https://arxiv.org/pdf/2202.02206.pdf) My starting point is this: ...
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### Variations in the output of quantile regression models

I am trying to implement quantile regression models with R for the first time (I am new to this regression approach). Here is the code that I am running: ...
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### How to interpret the quantile regression based on random forest?

I have read the Q&A how-are-the-results-of-multivariable-quantile-regression-interpreted and the recommended paper (Petscher and Logan, 2013). I have taken the Wine Quality Data Set, built the ...
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### Linear or quantile regression to deal with leverage points?

I'm doing a linear regression model, but even after the log-log transformation it contains many leverage points (outliers that are part of the data), the residuals are not normal and the variance is ...
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### How to calculate the correlation by the Spearman method for each quantile of the quantile regression in R?

I'm trying to calculate the Spearman's correlation coefficient for each quantile of my quantile regression (to later calculate the R² of each quantile), but the package I know of (QCSIS) uses Pearson'...
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### What are some methods for comparing 2 separate quantile regression curves?

I am currently working with a dataset using the QuantregGrowth package in RStudio to determine the 2.5th/97.5th percentile curves of a biomarker across the age spectrum. I have a pretty good handle on ...
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### OLS is BLUE (or BUE) to minimize MSE. Is quantile regression is BLUE to minimize MAE?

The Gauss-Markov theorem considers "best" as "lowest mean square error (MSE)" and a recent version of the theorem shows OLS is not only BLUE but also BUE: https://www.ssc.wisc.edu/~...
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### Why is there no panel quantile regression with two-way fixed effects yet?

I have been learning the quantile regression model recently, and my understanding is (possibly wrong) that quantile regression is essentially extracting the subsamples corresponding to a certain ...
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### How does the smoothing lambda is calculated in quantreg::rqss?

I have been working with quantreg::rqss() function for non-parametric quantile regression in R (documentation is here). And I have a question of what is happening ...
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### Residual using absolute loss linear regression

For ordinary least square linear regression, we have sum of residuals as zero, what about the sum of residuals for linear regression calculated using absolute loss?
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### Why "we would be way too confident" while the confidence interval is too small

I read about quantile regression and was confused about one sentence: "We would be way too confident" about confidence interval in this post (under the second figure): here. I think that the ...
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### Is it possible to use a Gibbs sampler for uncertainty propagation?

Situation: 10 basic numeric properties are predicted using quantile regression forest, then they are put into a desicion rule system to decide land management. The desicion rules result in one class (...
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### Goodness of fit of two models

My two models that I would like to compare are Weibull distribution and Quantile regression (in the case of Weibull distribution I have estimated the quantile curves). I would like to know if there is ...
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### Problem in performing quantile regression with quantreg [closed]

I am performing a censored quantile regression on survival data to account for time differences in survival at certain percentiles in my cohort. I am using the ...
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### Quantile regression showing different results with same tau

I am using the quantreg package from R to calculate quantile regression between 2 columns : red pixel values and near infrared pixel values (target). But the problem is that it gives me different ...
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### How does ordinal regression compare to quantile regression?

I am familiar with ordinal regression and quantile regression at a high level, but would like a deeper understanding of the two beginning on how they differ. Can someone compare and contrast the two, ...
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### Quantile regression on a constant: is this different from unconditional quantile?

With a linear model, estimating an OLS regression of y on a constant only will give us the mean of y. I was wondering whether ...
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### Is it possible to specify different quantile regression models for each quantile?

As the title says. I have never seen it, but I see no point that would prohibit me to do it. For example, a different set of variables might bear predictive value for the 25th-percentile of the ...
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### Hyperparameter tuning of quantile gradient boosting regression and linear quantile regression

I have am using Sklearns GradientBoostingRegressor for quantile regression as wells as a linear neural network implemented in Keras. I do however not know how to find the hyperparameters. For the ...
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