<p>Comparison of pseudo R-squares across quantile levels among 1) conventional quantile regression model (CQR), 2) threshold-based quantile regression model (TBQR), and 3) threshold-based quantile regression considering interaction effects (TBQRI).</p
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
Mean regression versus quantile regression I Most methods for studying covariate effects focus on me...
Abstract. Quantile regression is an evolving body of statistical methods for estimating and drawing ...
<p>Variations of Pseudo R-square across quantile levels of (a) the two most significant risk factors...
Modeling quantile regression coefficients functions permits describing the coefficients of a quanti...
Quantile regression model has caught a lot of attention lately in many areas including statistics an...
Comparison of the resultsa,b of the conditional quantile regression models by price range (N = 71,28...
BSquare in an R package to conduct Bayesian quantile regression for continuous, discrete, and censor...
The coefficients of a quantile regression model are one-to-one functions of the order of the quantil...
This article studies the relationship between the two most-used quantile models with endogeneity: th...
Normally the relationship between two variables x and y is studied using the linear regression equat...
Normally the relationship between two variables x and y is studied using the linear regression equat...
In ordinary quantile regression, quantiles of different order are estimated one at a time. An altern...
Residuals of fitting models: Comparison using Q-Q plots (left) and real vs. residual (right) for dif...
<p>Note: Numbers below the coefficients represent the Standard errors.</p><p>*** p<0.01,</p><p>** p<...
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
Mean regression versus quantile regression I Most methods for studying covariate effects focus on me...
Abstract. Quantile regression is an evolving body of statistical methods for estimating and drawing ...
<p>Variations of Pseudo R-square across quantile levels of (a) the two most significant risk factors...
Modeling quantile regression coefficients functions permits describing the coefficients of a quanti...
Quantile regression model has caught a lot of attention lately in many areas including statistics an...
Comparison of the resultsa,b of the conditional quantile regression models by price range (N = 71,28...
BSquare in an R package to conduct Bayesian quantile regression for continuous, discrete, and censor...
The coefficients of a quantile regression model are one-to-one functions of the order of the quantil...
This article studies the relationship between the two most-used quantile models with endogeneity: th...
Normally the relationship between two variables x and y is studied using the linear regression equat...
Normally the relationship between two variables x and y is studied using the linear regression equat...
In ordinary quantile regression, quantiles of different order are estimated one at a time. An altern...
Residuals of fitting models: Comparison using Q-Q plots (left) and real vs. residual (right) for dif...
<p>Note: Numbers below the coefficients represent the Standard errors.</p><p>*** p<0.01,</p><p>** p<...
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
Mean regression versus quantile regression I Most methods for studying covariate effects focus on me...
Abstract. Quantile regression is an evolving body of statistical methods for estimating and drawing ...