(2011), "Censored Quantile Regression With Covariate Measurement Errors," Statistica Sinica, 21, 949-971.Ma, Y., & Yin, G. (2011). Censored quantile regression with covariate measurement errors. Statistica Sinica, 21(2), 949-971.Ma Y, Yin G. Censored quantile regression with covariate ...
Quantile regressionInverse probability weightingIn this paper, we consider quantile regression estimation for linear models with covariate measurement errors and nonignorable missing responses. Firstly, the influence of measurement errors is eliminated through the bias-corrected quantile loss function. To ...
Prevention begins with the identification and raising awareness of stroke risk factors. To fill this gap, this study identified and quantified the effect of modifiable and non-modifiable predictors of stroke using a quantile regression approach in South Africa (SA). In SA, stroke is the second ...
The “xtivregress” command in Stata used for the analysis in this study help to achieve the two stages in a single estimation, and gives the corrected standard error directly. However, the first stage regression is also separately estimated in order to determine the suitability of the chosen ...
{c}\)at the same position as the corrected measurement. However, the estimates, particularly around the zero-positive change point, might not be stable. This is because the estimation of quantile regression is not stable at extreme percentiles. Around the change point, the percentile of non-...
error distribution like other conventional econometric methods that employ mean regression techniques such as Ordinary Least Squares (OLS) and Generalized Method of Moment (GMM) that assume errors are normally distributed. The moment quantile regression (MM-QR) is beneficial when the data is skewed ...
Maxi- mization step; ML: Maximum likelihood; QR: Quantile regression; QR-LMM: Quantile regression for linear mixed-effects models; SAEM: Stochastic Approxi- mation version of the EM algorithm; SE: Standard error; VL: Viral load refers to the number of HIV copies in a milliliter of blood ...
(2022) propose a theoretical model based on quantile regression and the DY spillover index to investigate how credit risk is interlinked among 18 sovereign countries. Abundant application of this model has been found in the literature (Chen et al.2022a; Billah et al.2022; Yousaf et al.2022;...
(2024). Wind power curve modelling: A probabilistic beta regression approach. Renewable Energy, 119970. Google Scholar Carroll et al., 2006 R.J. Carroll, D. Ruppert, L.A. Stefanski, C.M. Crainiceanu Measurement error in nonlinear models: a modern perspective, Chapman and Hall/CRC (2006...
4.6 Driscoll Kraay standard error The DKSE test employs the LCF as the dependent variable to determine the major variables influencing LCF (Table 8). The findings reveal six major factors: GDP, GDP2, forestry, financial inclusion, urbanization, and population. The DKSE regression results indicate...