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Article
Hierarchical linear regression models for conditional quantiles
The quantile regression has several useful features and therefore is gradually develo** into a comprehensive approach to the statistical analysis of linear and nonlinear response models, but it cannot deal e...
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Article
Approximate confidence interval construction for risk difference under inverse sampling
For studies with dichotomous outcomes, inverse sampling (also known as negative binomial sampling) is often used when the subjects arrive sequentially, when the underlying response of interest is acute, and/or wh...
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Article
Robust estimation in inverse problems via quantile coupling
In this article we consider a sequence of hierarchical space model of inverse problems. The underlying function is estimated from indirect observations over a variety of error distributions including those tha...
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Article
Lack-of-fit tests based on weighted ratio of residuals and variances
This article proposes a new lack-of-test based on the weighted ratio of residuals and variances for partially linear regression models. The large and small sampling properties of the proposed test are establis...
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Article
Simultaneous variable selection and parametric estimation for quantile regression
In this paper, variable selection techniques in the linear quantile regression model are mainly considered. Based on the penalized quantile regression model, a one-step procedure that can simultaneously perfor...
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Article
Heteroscedasticity Detection and Estimation with Quantile Difference Method
When dealing with regression analysis, heteroscedasticity is a problem that the authors have to face with. Especially if little information can be got in advance, detection of heteroscedasticity as well as est...
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Article
Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates
In this paper, we discuss Bayesian joint quantile regression of mixed effects models with censored responses and errors in covariates simultaneously using Markov Chain Monte Carlo method. Under the assumption ...
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Article
Adaptive quantile regression with precise risk bounds
An adaptive local smoothing method for nonparametric conditional quantile regression models is considered in this paper. Theoretical properties of the procedure are examined. The proposed method is fully adapt...
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Article
A New Method For Dynamic Stock Clustering Based On Spectral Analysis
In this paper, we propose a new method to classify the stock cluster based on the motions of stock returns. Specifically, there are three criteria: (1) The positive or negative signs of elements in the eigenve...
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Article
An effective method to reduce the computational complexity of composite quantile regression
In this article, we aim to reduce the computational complexity of the recently proposed composite quantile regression (CQR). We propose a new regression method called infinitely composite quantile regression (ICQ...
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Article
Quantile regression for linear models with autoregressive errors using EM algorithm
In this paper, we consider the quantile linear regression models with autoregressive errors. By incorporating the expectation–maximization algorithm into the considered model, the iterative weighted least squa...
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Article
Joint modeling for mixed-effects quantile regression of longitudinal data with detection limits and covariates measured with error, with application to AIDS studies
It is very common in AIDS studies that response variable (e.g., HIV viral load) may be subject to censoring due to detection limits while covariates (e.g., CD4 cell count) may be measured with error. Failure t...
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Article
Quantile Regression for Dynamic Panel Data Using Hausman–Taylor Instrumental Variables
This paper considers quantile regression for dynamic fixed effects panel data models with Hausman–Taylor instrumental variables (HTIV). The fixed effects estimators of panel data are typically biased when ther...
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Article
Bayesian Local Influence for Spatial Autoregressive Models with Heteroscedasticity
This paper studies Bayesian local influence analysis for the spatial autoregressive models with heteroscedasticity (heteroscedastic SAR models). Two local diagnostic procedures using curvature-based and slope-...
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Article
Open AccessExploration of the impact of political ideology disparity on COVID-19 transmission in the United States
Based on individual-level studies, previous literature suggested that conservatives and liberals in the United States had different perceptions and behaviors when facing the COVID-19 threat. From a state-level...
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Article
Open AccessPrediction study of electric energy production in important power production base, China
**njiang is an important power production base in China, and its electric energy production needs not only meet the demand of **njiang's electricity consumption, but also make up for the shortage of electricit...
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Article
Analysis of the effect of temperature on tuberculosis incidence by distributed lag non-linear model in Kashgar city, China
The aim of this study was to explore the effect of temperature on tuberculosis (TB) incidence using the distributed lag non-linear model (DLNM) from 2017 to 2021 in Kashgar city, the region with higher TB inci...
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Article
Open AccessDistinguishing the Vaccine Effectiveness of Inactivated BBIBP-CorV Vaccine Booster Against the Susceptibility, Infectiousness, and Transmission of Omicron Stains: A Retrospective Cohort Study in Urumqi, China
With COVID-19 vaccination rolled out globally, increasing numbers of studies have shown that booster vaccines can enhance an individual’s protection against the infection, hospitalization, and death caused by ...
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Article
Open AccessEffectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 infection: a matched cohort study of adult close contacts
Although COVID-19 vaccines and their booster regimens protect against symptomatic infections and severe outcomes, there is limited evidence about their protection against asymptomatic and symptomatic infection...
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Article
Estimation and variable selection for generalized functional partially varying coefficient hybrid models
In this article, we propose a novel class of generalized functional partially varying coefficient hybrid models and variable selection procedure in which the explanatory variables include infinite dimensional ...