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A pipelined Reed-Solomon decoder based on a modified step-by-step algorithm

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Frontiers of Information Technology & Electronic Engineering 2016年第9期17卷 954-961页

作者： Xing-ru PENG Wei ZHANG yan-yan liu School of Electronic and Information Engineering Tianjin UniversityTianjin 300072China College of Electronic Information and Optical Engineering Nankai UniversityTianjin 300071China

We propose a pipelined Reed-Solomon(RS) decoder for an ultra-wideband system using a modified stepby-step algorithm. To reduce the complexity, the modified step-by-step algorithm merges two cases of the original algorithm. The pipelined structure allows the decoder to work at high rates with minimum delay. Consequently, for RS(23,17) codes, the proposed architecture requires 42.5% and 24.4% less area compared with a modified Euclidean architecture and a pipelined degree-computationless modified Euclidean architecture, respectively. The area of the proposed decoder is 11.3% less than that of the previous step-by-step decoder with a lower critical path delay.

关键词： Reed-Solomon codes Step-by-step algorithm Ultra-wideband Pipelined structure

Semiparametric Empirical Likelihood Estimation for Two-stage Outcome-dependent Sampling under the Frame of Generalized Linear Models

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Acta Mathematicae Applicatae Sinica 2014年第3期30卷 663-676页

作者： Jie-li DING yan-yan liu School of Mathematics and Statistics Wuhan University

Epidemiologic studies use outcome-dependent sampling （ODS） schemes where, in addition to a simple random sample, there are also a number of supplement samples that are collected based on outcome variable. ODS scheme is a cost-effective way to improve study efficiency. We develop a maximum semiparametric empirical likelihood estimation （MSELE） for data from a two-stage ODS scheme under the assumption that given covariate, the outcome follows a general linear model. The information of both validation samples and nonvalidation samples are used. What is more, we prove the asymptotic properties of the proposed MSELE.

关键词： biased-sampling two-stage design empirical likelihood generalized linear models large-sample properties.

Additive Rate Model With Auxiliary Covariates

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Acta Mathematicae Applicatae Sinica 2017年第1期33卷 125-140页

作者： Zhi-bin XU Lu-qin liu yan-yan liu School of Mathematics and Statistics Wuhan University Wuhan 430072 China

In this paper, we consider an inference method for recurrent event data in which the primary exposure covariate is assessed only in a validation set, while as an auxiliary covariate for the main exposure is available for the full cohort. Additive rate model is considered. The existing estimating equations in the absence of primary exposure are corrected by taking use of the validation data and auxiliary information, which yield consistent and asymptotically normal estimators of the regression parameters. The estimated baseline mean process is shown to converge weakly to a zero-mean Gaussian process. Extensive simulations are conducted to evaluate finite sample performance.

关键词： additive rate model recurrent event data auxiliary covariate estimating equation validation set

Additive Hazards Regression with Random Effects for Clustered Failure Times

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Acta Mathematica Sinica,English Series 2015年第3期31卷 511-525页

作者： Deng PAN yan yan liu Yuan Shan WU Department of Statistics Chinese University of Hong Kong School of Mathematics and Statistics Wuhan University

Additive hazards model with random effects is proposed for modelling the correlated failure time data when focus is on comparing the failure times within clusters and on estimating the correlation between failure times from the same cluster, as well as the marginal regression parameters. Our model features that, when marginalized over the random effect variable, it still enjoys the structure of the additive hazards model. We develop the estimating equations for inferring the regression parameters. The proposed estimators are shown to be consistent and asymptotically normal under appropriate regularity conditions. Furthermore, the estimator of the baseline hazards function is proposed and its asymptotic properties are also established. We propose a class of diagnostic methods to assess the overall fitting adequacy of the additive hazards model with random effects. We conduct simulation studies to evaluate the finite sample behaviors of the proposed estimators in various scenarios. Analysis of the Diabetic Retinopathy Study is provided as an illustration for the proposed method.

关键词： Additive hazards regression clustered failure times counting process empirical process,frailty model checking random effects

Weighted Least Squares Method for the Accelerated Failure Time Model with Auxiliary Covariates

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Acta Mathematica Sinica,English Series 2019年第7期35卷 1163-1178页

作者： Ling Hui JIN yan yan liu Lang WU School of Mathematics and Statistics Wuhan University Wuhan 430072 P. R. China City College Wuhan University of Science and Technology Wuhan 430083 P. R. China Department of Statistics University of British Columbia Vancouver Canada

This paper deals with the analysis of accelerated failure time model when the primary covariate is subject to missing. We assume that the true covariate is measured precisely on a randomly chosen validation set, whereas auxiliary information for primary covariate is available to all study subjects. The asymptotic properties for the proposed estimator are developed and the simulation studies show that the efficiency gain is remarkable compared to the method using only the validation sample. A real example is also provided as an illustration.

关键词： Survival analysis accelerated failure time model auxiliary covariates validation sample weighted least squares estimation

Optimal Generalized Case-Cohort Analysis with Cox's Proportional Hazards Model

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Acta Mathematicae Applicatae Sinica 2015年第3期31卷 841-854页

作者： YONG-XIU CAO JI-CHANG YU yan-yan liu School of Mathematics and Statistics Wuhan University School of Statistics and Mathematics Zhongnan University of Economics and Law

Generalized case-cohort design has been proved to be a cost-effective way to enhance the efficiency of large epidemiological cohort. In this article, we propose an inference procedure for estimating the unknown parameters in Cox＇s proportional hazards model in generalized case-cohort design and establish an optimal sample size allocation to achieve the maximum power at a given budget. The finite sample performance of the proposed method is evaluated through simulation studies. The proposed method is applied to a real data set from the National Wilm＇s Tumor Study Group.

关键词： Cox's proportional hazards model generalized case-cohort optimal allocation

A New Robust Risk Measure:Quantile Shortfall

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Acta Mathematica Sinica,English Series 2020年第9期36卷 1014-1024页

作者： You Li CHEN yan yan liu Guang Cai MAO Yuan Shan WU Fei yan Law School Wuhan UniversityWuhan 430072P.R.China School of Mathematics and Statistics Wuhan UniversityWuhan 430072P.R.China School of Mathematics and Statistics Central China Normal UniversityWuhan 430079P.R.China School of Statistics and Mathematics Zhongnan University of Economics and LawWuhan 430073P.R.China

Among recent measures for risk management,value at risk(VaR)has been criticized because it is not coherent and expected shortfall(ES)has been criticized because it is not robust to ***,[***.,38,393–417(2013)]proposed a risk measure called median shortfall(MS)which is distributional robust and easy to *** this paper,we propose a more generalized risk measure called quantile shortfall(QS)which includes MS as a special *** measures the conditional quantile loss of the tail risk and inherits the merits of *** construct an estimator of the QS and establish the asymptotic normality behavior of the *** simulation shows that the newly proposed measures compare favorably in robustness with other widely used measures such as ES and VaR.

关键词： Nonparametric estimation quantile shortfall risk measure robust

The Proportional Mean Residual Life Regression Model with Cure Fraction and Auxiliary Covariate

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Acta Mathematicae Applicatae Sinica 2022年第2期38卷 312-323页

作者： Shao-jia JIN yan-yan liu Guang-cai MAO Ming-yu SHAN School of Mathematics and Statistics Wuhan UniversityWuhan 430072China School of Mathematics and Statistics Central China Normal UniversityWuhan 430079China

As biological studies become more expensive to conduct,it is a frequently encountered question that how to take advantage of the available auxiliary covariate information when the exposure variable is not *** this paper,we propose an induced cure rate mean residual life time regression model to accommodate the survival data with cure fraction and auxiliary covariate,in which the exposure variable is only assessed in a validation set,but a corresponding continuous auxiliary covariate is ascertained for all subjects in the study *** studies elucidate the practical performance of the proposed method under finite *** an illustration,we apply the proposed method to a heart disease data from the Study of Left Ventricular Dysfunction.

关键词： auxiliary covariate Kernel smoothing logistic regression mean residual life mixture cure model

SICA for Cox's Proportional Hazards Model with a Diverging Number of Parameters

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Acta Mathematicae Applicatae Sinica 2014年第4期30卷 887-902页

作者： Yue-Yong SHI Yong-Xiu CAO Yu-Ling JIAO yan-yan liu School of Mathematics and Statistics Wuhan University

The smooth integration of counting and absolute deviation （SICA） penalized variable selection procedure for high-dimensional linear regression models is proposed by Lv and Fan （2009）. In this article, we extend their idea to Cox＇s proportional hazards （PH） model by using a penalized log partial likelihood with the SICA penalty. The number of the regression coefficients is allowed to grow with the sample size. Based on an approximation to the inverse of the Hessian matrix, the proposed method can be easily carried out with the smoothing quasi-Newton （SQN） algorithm. Under appropriate sparsity conditions, we show that the resulting estimator of the regression coefficients possesses the oracle property. We perform an extensive simulation study to compare our approach with other methods and illustrate it on a well known PBC data for predicting survival from risk factors.

关键词： Cox proportional hazards models penalized partial likelihood diverging parameters oracle prop-erty smoothing quasi-Newton