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| 1 | Statistical inference for zero-and-one-inflated poisson models显示文摘In this paper, a zero-and-one-inflated Poisson (ZOIP) model is studied. The maximum likelihoodestimation and the Bayesian estimation of the model parameters are obtained based on dataaugmentation method. A simulation study based on proposed sampling algorithm is conductedto assess the performance of the proposed estimation for various sample sizes. Finally, two realdata-sets are analysed to illustrate the practicability of the proposed method. | Yincai Tang Wenchen Liu Ancha Xu | 2017 | Statistical Theory and Related Fields2017，1，2： | 5 |
| 2 | A New Way to Estimate The Parameters in the Progresive Stres Acelerated Life Testing显示文摘ANewWaytoEstimateTheParametersintheProgresiveStresAceleratedLifeTesting*TangYincaiandFeiHeliangAbstract.Amongthethreetypesofa... | Tang Yincai and Fei Heliang | 1996 | Applied Mathematics(A Journal of Chinese Universities)1996，11，4： | 2 |
| 3 | EM algorithm for degradation dataanalysis 显示文摘 | Xu Ancha Tang Yincai | 2010 | Journal of China Normal University2010，，5： | 1 |
| 4 | Design of Experiment in Global Sensitivity Analysis Basedon ANOVA High-Dimensional Model Representation显示文摘 | Xiaodi Wang Yincai Tang Xueping Chen and Yingshan Zhang | 2010 | Commucation in statistics-Simulation and Compucation2010，39，6： | 1 |
| 5 | Approximated Parameter Estimation of Three-parameter Log-normal Distributions Based on Generalized Least Squares Method显示文摘 | Tang Yincai | 2001 | Journal of Shanghai2001，4，： | 1 |
| 6 | Orthogonal arrays for the estimation of global sensitivity indices based on hign-dimension model representation显示文摘 | Xiaodi Wang Yincai Tang Yingshan Zhang | 2011 | Communicasions in statistics-simulation and computation2011，40，9： | 1 |
| 7 | Design of experiment in global sensitivity analysis based on ANOVA high-dimension model representation显示文摘 | Wang Xiaodi Tang Yincai Chen Xueping | 2010 | Communicasions in Statistics-Simulation and Computation2010，39，6： | 1 |
| 8 | Orthogonal arrays for the estimation of global sensitivity indices based on ANOVA high-dimension model representation显示文摘 | Wang Xiaodi Tang Yincai Zhang Yingshan | 2011 | Communicasions in Statistics-Simulation and Computation2011，40，9： | 1 |
| 9 | Design of Experiment in Global Sensitivity Analysis Based on ANOVA High-Dimensional Model Representation显示文摘 | Xiaodi Wang Yincai Tang Xueping Chen and Yingshan Zhang | 2010 | Commucation in statistics-Simulation and Compucation2010，39，6： | 1 |
| 10 | Orthogonal arrays for the estimation of global sensitivity indices based on hign- dimension model representation显示文摘 | Xiaodi Wang Yincai Tang Yingshan Zhang | 2011 | Communicasions in statistics- simulation and computation2011，40，9： | 1 |
| 11 | Commentary: The Khamis-Higgins Model显示文摘 | XU Haiyan TANG Yincai | 2003 | IEEE Transactions on Reliability2003，52，1： | 1 |
| 12 | Editorial Foreword显示文摘It is our great pleasure to announce that the Statistical Theory and Related Fields(STARF),sponsored by East China Normal University,has been recently granted a CN number by the National Press and Publication Administration of China and obtained a publishing license issued by Shanghai Press and Publication Administration.This issue is the first issue(创刊号)of STARF as it becomes a CN registered academic journal in China. | Jun Shao Yincai Tang | 2021 | Statistical Theory and Related Fields2021，5，3： | 0 |
| 13 | An integrated epidemic modelling framework for the real-time forecast of COVID-19 outbreaks in current epicentres显示文摘Various studies have provided a wide variety of mathematical and statistical models for early epidemic prediction of the COVID-19 outbreaks in China's Mainland and other epicentres worldwide.In this paper,we present an integrated modelling framework,which incorporates typical exponential growth models,dynamic systems of compartmental models and statistical approaches,to depict the trends of COVID-19 spreading in 33 most heavily suffering countries.The dynamic system of SIR-X plays the main role for estimation and prediction of the epidemic trajectories showing the effectiveness of containment measures,while the other modelling approaches help determine the infectious period and the basic reproduction number.The modelling framework has reproduced the subexponential scaling law in the growth of confirmed cases and adequate fitting of empirical time-series data has facilitated the efficient forecast of the peak in the case counts of asymptomatic or unidentified infected individuals,the plateau that indicates the saturation at the end of the epidemic growth,as well as the number of daily positive cases for an extended period. | Jiawei Xu Yincai Tang | 2021 | Statistical Theory and Related Fields2021，5，3： | 0 |
| 14 | Research on three-step accelerated gradient algorithm in deep learning显示文摘Gradient descent(GD)algorithm is the widely used optimisation method in training machine learning and deep learning models.In this paper,based on GD,Polyak’s momentum(PM),and Nesterov accelerated gradient(NAG),we give the convergence of the algorithms from an ini-tial value to the optimal value of an objective function in simple quadratic form.Based on the convergence property of the quadratic function,two sister sequences of NAG’s iteration and par-allel tangent methods in neural networks,the three-step accelerated gradient(TAG)algorithm is proposed,which has three sequences other than two sister sequences.To illustrate the perfor-mance of this algorithm,we compare the proposed algorithm with the three other algorithms in quadratic function,high-dimensional quadratic functions,and nonquadratic function.Then we consider to combine the TAG algorithm to the backpropagation algorithm and the stochastic gradient descent algorithm in deep learning.For conveniently facilitate the proposed algorithms,we rewite the R package‘neuralnet’and extend it to‘supneuralnet’.All kinds of deep learning algorithms in this paper are included in‘supneuralnet’package.Finally,we show our algorithms are superior to other algorithms in four case studies. | Yongqiang Lian Yincai Tang Shirong Zhou | 2022 | Statistical Theory and Related Fields2022，6，1： | 0 |
| 15 | Semiparametric estimation for accelerated failure time mixture cure model allowing non-curable competing risk显示文摘The mixture cure model is the most popular model used to analyse the major event with a potential cure fraction.But in the real world there may exist a potential risk from other non-curable competing events.In this paper,we study the accelerated failure time model with mixture cure model via kernel-based nonparametric maximum likelihood estimation allowing non-curable competing risk.An EM algorithm is developed to calculate the estimates for both the regression parameters and the unknown error densities,in which a kernel-smoothed conditional profile likelihood is maximised in the M-step,and the resulting estimates are consistent.Its performance is demonstrated through comprehensive simulation studies.Finally,the proposed method is applied to the colorectal clinical trial data. | Yijun Wang Jiajia Zhang Yincai Tang | 2020 | Statistical Theory and Related Fields2020，4，1： | 0 |
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