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Identification of Linear Systems Using Binary Sensors with Random Thresholds: 《Journal of Systems Science & Complexity》2024年第3期907-923,共17页HUANG Zhiyong SONG Qijiang; In this paper,the problem of identifying autoregressive-moving-average systems under random threshold binary-valued output measurements is considered.With the help of stochastic approximation algorithms with expanding...; 关键词：Α-MIXING binary sensor quantized system stochastic approximation stochastic thresh-old strongly consistent system identification

Uncertainty Comparison Between Value-at-Risk and Expected Shortfall: 《Communications in Mathematical Research》2024年第1期102-124,共23页Qing Liu Weimin Liu Liang Peng Gengsheng Qin; Value-at-Risk(VaR)and expected shortfall(ES)are two key risk measures in financial risk management.Comparing these two measures has been a hot debate,and most discussions focus on risk measure properties.This paper us...; 关键词：Α-MIXING asymptotic variance expected shortfall VALUE-AT-RISK

The Asymptotic Distributions of the Largest Entries of Sample Correlation Matrices under an α-mixing Assumption: 《Acta Mathematica Sinica,English Series》2022年第11期2039-2056,共18页Hao Zhu ZHAO Yong ZHANG; National Natural Science Foundation of China(Grant Nos.11771178 and 12171198);the Science and Technology Development Program of Jilin Province(Grant No.20210101467JC);Science and Technology Program of Jilin Educational Department during the“13th Five-Year”Plan Period(Grant No.JJKH20200951KJ);Fundamental Research Funds for the Central Universities。; Let{Xk,i;k≥1,i≥1}be an array of random variables,{Xk;k≥1}be a strictly stationaryα-mixing sequence,where Xk=(Xk,1,Xk,2,...).Let{pn;n≥1}be a sequence of positive integers such that c1≤p n n≤c2,where c1,c2>0.In t...; 关键词：Sample correlation matrices α-mixing sequence Chen-Stein method

Improved Hoeffding inequality for dependent bounded or sub-Gaussian random variables: 《Probability, Uncertainty and Quantitative Risk》2021年第1期53-60,共8页Yuta Tanoue; This work was supported by JSPS Grant-in-Aid for Young Scientists(Grant No.18K12873);Waseda University Grants for Special Research Projects(“Tokutei Kadai”)(Grant No.2019C-688).; When addressing various financial problems,such as estimating stock portfolio risk,it is necessary to derive the distribution of the sum of the dependent random variables.Although deriving this distribution requires i...; 关键词：α-mixing coefficient Hoeffding inequality BOUNDED SUB-GAUSSIAN

Identification of Errors-in-Variables Systems with General Nonlinear Output Observations and with ARMA Observation Noises被引量：1: 《Journal of Systems Science & Complexity》2020年第1期1-14,共14页SONG Qijiang HUANG Zhiyong; supported by the National Natural Science Foundation of China under Grant No.11571362.; This paper concerns the identification problem of scalar errors-in-variables(EIV)systems with general nonlinear output observations and ARMA observation noises.Under independent and identically distributed(i.i.d.)Gaus...; 关键词：ARMA noise Α-MIXING binary sensor ERRORS-IN-VARIABLES NONLINEAR OBSERVATION recursive estimate stochastic approximation(SA) strongly consistent system IDENTIFICATION

Unified Asymptotic Results for Maximum Spacing and Generalized Spacing Methods for Continuous Models被引量：1: 《Open Journal of Statistics》2018年第3期614-639,共26页Andrew Luong; Asymptotic results are obtained using an approach based on limit theorem results obtained for α-mixing sequences for the class of general spacings (GSP) methods which include the maximum spacings (MSP) method. The MS...; 关键词：MAXIMUM Product of SPACINGS M-ESTIMATORS QUASI-LIKELIHOOD Ratio Test Statistic Α-MIXING Sequences

Conditional Quantile Estimation with Truncated,Censored and Dependent Data: 《Chinese Annals of Mathematics,Series B》2015年第6期969-990,共22页Hanying LIANG Deli LI Tianxuan MIAO; supported by the National Natural Science Foundation of China(No.11271286);the Specialized Research Fund for the Doctor Program of Higher Education of China(No.20120072110007);a grant from the Natural Sciences and Engineering Research Council of Canada; This paper deals with the conditional quantile estimation based on left-truncated and right-censored data.Assuming that the observations with multivariate covariates form a stationary α-mixing sequence,the authors de...; 关键词：Berry-Esseen-type bound Conditional quantile estimator Strong rep-resentation Truncated and censored data Α-MIXING

EMPIRICAL LIKELIHOOD FOR LONGITUDINAL PARTIALLY LINEAR MODEL WITH α-MIXING ERRORS被引量：3: 《Journal of Systems Science & Complexity》2013年第2期232-248,共17页FAN Guoliang LIANG Hanying; supported by the National Natural Science Foundation of China under Grant Nos.11271286,11271286,71171003,and 11226218;Provincial Natural Science Research Project of Anhui Colleges under Grant No.KJ2011A032;Anhui Provincial Natural Science Foundation under Grant Nos.1208085QA04 and 10040606Q03; This paper considers large sample inference for the regression parameter in a partially linear regression model with longitudinal data and a-mixing errors. The authors introduce an estimated empirical likelihood for t...; 关键词：Confidence region empirical likelihood longitudinal data partially linear model a-mixingsequence.

Asymptotic Normality of Wavelet Density Estimator under Censored Dependent Observations: 《Acta Mathematicae Applicatae Sinica》2012年第4期781-794,共14页Si-li NIU; Supported by the National Natural Science Foundation of China (No.10871146); In this paper, we discuss the asymptotic normality of the wavelet estimator of the density function based on censored data, when the survival and the censoring times form a stationary α-mixing sequence. To simulate t...; 关键词：Wavelet density estimator asymptotic normality censored data α-mixing random weightedestimator

ASYMPTOTIC NORMALITY OF WAVELET ESTIMATOR IN HETEROSCEDASTIC MODEL WITH α-MIXING ERRORS被引量：3: 《Journal of Systems Science & Complexity》2011年第4期725-737,共13页Hanying LIANG; supported by the National Natural Science Foundation of China under Grant No.10871146;the Grant MTM2008-03129 from the Spanish Ministry of Science and Innovation; Consider heteroscedastic regression model Yni= g（xni）＋ σniεni （1 〈 i 〈 n）, where σ2ni= f（uni）, the design points （xni, uni） are known and nonrandom, g（.） and f（.） are unknown functions defined on cl...; 关键词：Α-MIXING asymptotic normality heteroscedastic regression model wavelet estimator.

Α-MIXING