Directional Regression Quantile Computation
However, there is few discussion on quantile regression for longitudinal data with both missing responses and measurement errors, which are commonly seen in practice. We develop a weighted and bias-corrected quantile loss function for the quantile regression with longitudinal data, which allows both ...
Quantile Regression workflow: first example Here is a Quantile Regression (QR) workflow specification: qrmon2 <-eval(expr =to_QRMon_R_command("create from dfTemperatureData;compute quantile regression with 12 knots and probabilities 0.25, 0.5, and 0.75;show date list plot with date origin 1900-...
(2017). Exact computation of gmm estimators for instrumental variable quantile regression models. arXiv preprint arXiv:1703.09382.Chen, L.-Y., Lee, S., 2017. Exact computation of GMM estimators for instrumental variable quantile regression models, working paper, available at https://arxiv.org/...
E [yi jxi ] = β0 + β1xi E [jyi β0 β1xi j jxi ] = γ0 + γ1xi Qu (τjxi ) can be estimated from the scaled errors yi β0 β1xi γ0 + γ1xi This provides a way to estimate quantile regression using two OLS regressions and the computation of a univariate quantile. ...
Computation • All computations involving data are performed in floating-point; therefore, all data provided must havetype/realconsand all returned solutions are floating-point, even if the problem is specified with exact values. • By default, all computations involving random variables are perform...
Bayesian Tobit quantile regression using g-prior distribution with ridge parameter[J] . Rahim Alhamzawi,Keming Yu.Journal of Statistical Computation and Simulation . 2015 (14)Alhamazawi, R. & Yu, K. (2015). Bayesian Tobit quantile regression using g-prior distribution with ridge parameter. J....
Extreme quantile regression provides estimates of conditional quantiles outside the range of the data. Classical quantile regression performs poorly in suc
Censored quantile regressionAalen estimatorExport durationExisting literature on censored quantile regression requires global linearity, bandwidth selection, or complex computation. In the current study, we propose weighted quantile regression for censored......
Hence, this motivates the use of a panel quantile regression estimation approach in the analysis of the fiscal discipline-fiscal federalism nexus in this study. Against this background, this study aims to shed more light on the relationship between fiscal federalism and fiscal discipline from a ...