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A Constrained Interval-Valued Linear Regression Model:A New Heteroscedasticity Estimation Method

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Journal of Systems Science & Complexity 2020年第6期33卷 2048-2066页

作者： ZHONG Yu zhang zhongzhan LI Shoumei Beijing University of Technology College of Applied SciencesBeijing 100020China

Linear regression models for interval-valued data have been widely *** literatures are to split an interval into two real numbers,i.e.,the left-and right-endpoints or the center and radius of this interval,and fit two separate real-valued or two dimension linear regression *** paper is focused on the bias-corrected and heteroscedasticity-adjusted modeling by imposing order constraint to the endpoints of the response interval and weighted linear least squares with estimated covariance matrix,based on a generalized linear model for interval-valued data.A three step estimation method is *** conclusions and numerical evaluations show that the proposed estimator has higher efficiency than previous estimators.

关键词： Conditional maximum likelihood estimation interval-valued data order constraint truncated normal distribution weighted least squares estimation

A Nonparametric Model Checking Test for Functional Linear Composite Quantile Regression Models

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Journal of Systems Science & Complexity 2024年第4期37卷 1714-1737页

作者： XIA Lili DU Jiang zhang zhongzhan Faculty of Science Beijing University of TechnologyBeijing 100124China

This paper is focused on the goodness-of-fit test of the functional linear composite quantile regression model.A nonparametric test is proposed by using the orthogonality of the residual and its conditional expectation under the null *** proposed test statistic has an asymptotic standard normal distribution under the null hypothesis,and tends to infinity in probability under the alternative hypothesis,which implies the consistency of the ***,it is proved that the test statistic converges to a normal distribution with nonzero mean under a local alternative *** simulations are reported,and the results show that the proposed test has proper sizes and is sensitive to the considered model *** proposed methods are also applied to two real datasets.

关键词： Composite quantile regression consistent test functional data nonparametric test quadratic form

SEMIPARAMETRIC ANALYSIS OF ISOTONIC ERRORS-IN-VARIABLES REGRESSION MODELS WITH RANDOMLY RIGHT CENSORED RESPONSE

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Journal of Systems Science & Complexity 2013年第3期26卷 441-461页

作者： SUN Zhimeng zhang zhongzhan DU Jiang School of Statistics Central University of Finance and Economics Beijing 100081 China College of AppliedSciences Beijing University of Technology Beijing 100124 China

This paper considers the estimation of a semiparametric isotonic regression model when the covariates are measured with additive errors and the response is randomly right censored by a censoring *** authors show that the proposed estimator of the regression parameter is rootn consistent and asymptotically *** authors also show that the isotonic estimator of the functional component,at a fixed point,is cubic root-n consistent and converges in distribution to the slope at zero of the greatest convex minorant of the sum of a two-sided standard Brownian motion and the square of the time parameter.A simulation study is carried out to investigate the performance of the estimators proposed in this article.

关键词： Estimation isotonic regression measurement errors randomly right censored semiparametric.

Randomized statistical inference:A unified statistical inference frame of frequentist,fiducial,and Bayesian inference

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Science China Mathematics 2020年第5期63卷 1007-1028页

作者： zhongzhan zhang Jiajia Dai Zhenhai Yang Department of Statistics Beijing University of TechnologyBeijing 100124China School of Mathematics and Statistics Guizhou UniversityGuiyang 550025China

We propose randomized inference(RI),a new statistical inference *** may be realized through a randomized estimate(RE)of a parameter vector,which is a random vector that takes values in the parameter space with a probability density function(PDF)that depends on the sample or sufficient statistics,such as the posterior distributions in Bayesian *** on the PDF of an RE of an unknown parameter,we propose a framework for both the vertical density representation(VDR)test and the construction of a confidence *** approach is explained with the aid of *** the equality hypothesis of multiple normal means without the condition of variance homogeneity,we present an exact VDR test,which is shown as an extension of one-way analysis of variance(ANOVA).In the case of two populations,the PDF of the Welch statistics is given by using the ***,through simulations,we show that the empirical distribution function,the approximated t,and the RE distribution function of Welch statistics are almost *** VDR test of the homogeneity of variance is shown to be more efficient than both the Bartlett test and the revised Bartlett ***,we discuss the prospects of RI.

关键词： confidence distribution pivot randomized inference vertical density representation VDR test

An Alternative Doubly Robust Estimation in Causal Inference Model

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Communications in Mathematics and Statistics 2024年第4期12卷 659-678页

作者： Shaojie Wei Gaorong Li zhongzhan zhang Faculty of Science Beijing University of TechnologyBeijing 100124People’s Republic of China School of Statistics Beijing Normal UniversityBeijing 100875People’s Republic of China

Doubly robust(DR)methods that employ both the propensity score and outcome models are widely used to estimate the causal effect of a treatment and generally outperform those methods only using the propensity score or the outcome ***,without appropriately chosen the working models,DR estimators may substantially lose *** this paper,based on the augmented inverse probability weighting procedure,we derive a new estimating equation for the causal effect by the strategy of combining estimating *** resulting estimator by solving the new estimating equation retains doubly robust and can improve the efficiency under the misspecification of conditional mean working *** further show the large sample properties of the proposed estimator under some regularity *** simulation experiments and a real data analysis,we illustrate that the proposed method is competitive with its competitors,which is in line with those implied by the asymptotic theory.

关键词： Average treatment effect Causal effect Doubly robust method Estimating equation Inverse probability weighting Semiparametric efficiency

Testing against second-order stochastic dominance of multiple distributions

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International Journal of Biomathematics 2015年第3期8卷 225-236页

作者： Jianling zhang zhongzhan zhang Weizhen Wang College of Applied Sciences Beijing University of Technology 100 Pingleyuan Chaoyang District Beijing 100124 P. R. China School of Mathematics and Information Sciences Weifang University Weifang 261061 P. R. China Department of Mathematics and StatisticsWright State University Dayton OH 45435 USA

Second-order stochastic dominance plays an important role in reliability and various branches of economics such as finance and decision-making under risk, and statistical testing for the stochastic dominance is often useful in practice. In this paper, we present a test of stochastic equality under the constraint of second-order stochastic dominance based on the theory of empirical processes. The asymptotic distribution of the test statistic is obtained, and a simple method to compute the critical value is derived. Simulation results and real data examples are presented to illustrate the proposed test method.

关键词： Second-order stochastic dominance asymptotic distribution hypothesis testing weak convergence.

VARIABLE SELECTION FOR PARTIALLY LINEAR VARYING COEFFICIENT QUANTILE REGRESSION MODEL

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International Journal of Biomathematics 2013年第3期6卷 67-80页

作者： JIANG DU zhongzhan zhang ZHIMENG SUN College of Applied Sciences Beijing University of Technology Beijing 100124 P. R. China School of Statistics Central University of Finance and Economics Beijing 100081 P. R. China

In this paper, we propose a variable selection procedure for partially linear varying coef- ficient model under quantile loss function with adaptive Lasso penalty. The functional coefficients are estimated by B-spline approximations. The proposed procedure simul- taneously selects significant variables and estimates unknown parameters. The major advantage of the proposed procedures over the existing ones is easy to implement using existing software, and it requires no specification of the error distributions. Under the regularity conditions, we show that the proposed procedure can be as efficient as the Oracle estimator, and derive the optimal convergence rate of the functional coefficients. A simulation study and a real data application are undertaken to assess the finite sample performance of the proposed variable selection procedure.

关键词： Quantile regression variable selection adaptive Lasso B-spline.

Statistical inference in the partial functional linear expectile regression model

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Science China Mathematics 2022年第12期65卷 2601-2630页

作者： Juxia Xiao Ping Yu Xinyuan Song zhongzhan zhang Faculty of Science Beijing University of TechnologyBeijing 100124China School of Mathematics and Computer Science Shanxi Normal UniversityTaiyuan 030092China Department of Statistics The Chinese University of Hong KongHong Kong 999077China

As extensions of means, expectiles embrace all the distribution information of a random *** expectile regression is computationally friendlier because the asymmetric least square loss function is differentiable everywhere. This regression also enables effective estimation of the expectiles of a response variable when potential explanatory variables are given. In this study, we propose the partial functional linear expectile regression model. The slope function and constant coefficients are estimated by using the functional principal component basis. The convergence rate of the slope function and the asymptotic normality of the parameter vector are established. To inspect the effect of the parametric component on the response variable, we develop Wald-type and expectile rank score tests and establish their asymptotic properties. The finite performance of the proposed estimators and test statistics are evaluated through simulation study. Results indicate that the proposed estimators are comparable to competing estimation methods and the newly proposed expectile rank score test is useful. The methodologies are illustrated by using two real data examples.

关键词： expectile regression functional principal component analysis Wald-type test expectile rank score test heteroscedasticity

A ROBUST ESTIMATOR OF MULTIVARIATE LOCATION BASED ON PROJECTION

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Applied Mathematics:A Journal of Chinese Universities 1999年第2期 36-46页

作者： zhang zhongzhan\ Li Guoying

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