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Testing serial correlation for partially nonlinear models
Zhan-Gong Zhou,Wei-Min Qian,Chen He 한국통계학회 2010 Journal of the Korean Statistical Society Vol.39 No.4
Partially nonlinear models, as extensions of partially linear models are extensively used in statistical modeling. This paper considers the spline empirical log-likelihood ratio for testing serial correlation in partially nonlinear models. It is shown that the proposed empirical log-likelihood ratio converges to the standard chi-square distribution under the null hypothesis of no serial correlation. Some simulations are conducted to estimate the rejection probabilities under the null hypothesis and serial correlation. An example of application is also illustrated.
Single-index composite quantile regression
Jiang, Rong,Zhou, Zhan-Gong,Qian, Wei-Min,Shao, Wen-Qiong 한국통계학회 2012 Journal of the Korean Statistical Society Vol.41 No.3
In this paper, we extend the composite quantile regression (CQR) method to a single-index model. The unknown link function is estimated by local composite quantile regression and the parametric index is estimated through the linear composite quantile. It is shown that the proposed estimators are consistent and asymptotically normal. The simulation studies and real data applications are conducted to illustrate the finite sample performance of the proposed methods.
Single-index composite quantile regression
Rong Jiang,Zhan-Gong Zhou,Wei-Min Qian,Wen-Qiong Shao 한국통계학회 2012 Journal of the Korean Statistical Society Vol.41 No.3
In this paper, we extend the composite quantile regression (CQR) method to a single-index model. The unknown link function is estimated by local composite quantile regression and the parametric index is estimated through the linear composite quantile. It is shown that the proposed estimators are consistent and asymptotically normal. The simulation studies and real data applications are conducted to illustrate the finite sample performance of the proposed methods.
Testing for the parametric component of partially linear EV models under random censorship
Linjun Tang,Changchun Wu,Zhan-Gong Zhou 한국통계학회 2014 Journal of the Korean Statistical Society Vol.43 No.2
This paper investigates the hypothesis test of the parametric component in partiallylinear errors-in-variables (EV) model with random censorship. We construct two teststatistics based on the difference of the corrected residual sum of squares and empiricallikelihood ratio under the null and alternative hypotheses. It is shown that the limitingdistributions of the proposed test statistics are both weighted sum of independent standardchi-squared distribution with one degree of freedom under the null hypothesis. Based onthe adjusted test statistics, we further develop two new types of test procedures. Finitesample performance of the proposed test procedures is evaluated by extensive simulationstudies.
Estimation and inference of combining quantile and least-square regressions with missing data
Linjun Tang,Shengchao Zheng,Zhan-Gong Zhou 한국통계학회 2018 Journal of the Korean Statistical Society Vol.47 No.1
In this paper, we consider how to incorporate quantile information to improve estimator efficiency for regression model with missing covariates. We combine the quantile information with least-squares normal equations and construct an unbiased estimating equations (EEs). The lack of smoothness of the objective EEs is overcome by replacing them with smooth approximations. The maximum smoothed empirical likelihood (MSEL) estimators are established based on inverse probability weighted (IPW) smoothed EEs and their asymptotic properties are studied under some regular conditions. Moreover, we develop two novel testing procedures for the underlying model. The finite-sample performance of the proposed methodology is examined by simulation studies. A real example is used to illustrate our methods.
Yang, Dang-Wei,Ma, Zhan-Guo,Qi, Fu-Zhou,Gong, Peng,Liu, Dao-Ping,Zhao, Guo-Zhen,Zhang, Ray Ruichong Techno-Press 2017 Geomechanics & engineering Vol.13 No.2
This paper proposes gob-side entry retaining by roof break and filling in thick-layer soft rock conditions based on the thick-layer soft rock roof strata migration law and the demand for non-pillar gob-side entry retaining projects. The functional expressions of main roof subsidence are derived for three break roof direction conditions: lateral deflection toward the roadway, lateral deflection toward the gob and vertically to the roof. These are derived according to the load-bearing boundary conditions of the main roadway roof stratum. It is concluded that the break roof angle is an important factor influencing the stability of gob-side entry retaining surrounding rock. This paper studies the stress distribution characteristics and plastic damage scope of gob-side entry retaining integrated coal seams, as well as the roof strata migration law and the supporting stability of caving structure filled on the break roof layer at the break roof angles of $-5^{\circ}$, $0^{\circ}$, $5^{\circ}$, $10^{\circ}$ and $15^{\circ}$ are studied. The simulation results of numerical analysis indicate that, the stress concentration and plastic damage scope to the sides of gob-side entry retaining integrated coal at the break roof angle of $5^{\circ}$ are reduced and shearing stress concentration of the caving filling body has been eliminated. The disturbance of coal mining to the roadway roof and loss of carrying capacity are mitigated. Field tests have been carried out on air-return roadway 5203 with the break roof angle of $5^{\circ}$. The monitoring indicates that the break roof filling section and compaction section are located at 0-45 m and 45-75 m behind the working face, respectively. The section from 75-100 m tends to be stable.