检索结果-南通市图书馆

Optimal Grouping of Heterogeneous Components in Series and Parallel Systems Under Archimedean Copula Dependence

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2022年第3期35卷 1030-1051页

作者： FANG Longxiang ZHANG Xinsheng JIN Qing department of Mathematics and statistics Anhui Normal UniversityWuhu 241000China Department of Statistics Fudan UniversityShanghai 200433China

This paper considers series and parallel systems comprising n components drawn from a heterogeneous population consisting of m different subpopulations.The components within each subpopulation are assumed to be dependent,while the subpopulations are independent of each other.The authors also assume that the subpopulations have different Archimedean copulas for their dependence.Under this setup,the authors discuss the series and parallel systems reliability for three different cases,respectively.The authors use the theory of stochastic orders and majorization to establish the main results,and finally present some numerical examples to illustrate all the results established here.

关键词： Archimedean copula majorization parallel system reliability Schur-convex/concave function series system stochastic orders

High-Dimensional Volatility Matrix Estimation with Cross-Sectional Dependent and Heavy-Tailed Microstructural Noise

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2023年第5期36卷 2125-2154页

作者： LIANG Wanwan WU Ben FAN Xinyan JING Bingyi ZHANG Bo Center for Applied statistics School of StatisticsInstitute of Probability and StatisticsRenmin University of ChinaBeijing 100086China Department of Statistics&Data Science Southern University of Science and TechnologyShenzhen 518055China

The estimates of the high-dimensional volatility matrix based on high-frequency data play a pivotal role in many financial applications.However,most existing studies have been built on the sub-Gaussian and cross-sectional independence assumptions of microstructure noise,which are typically violated in the financial markets.In this paper,the authors proposed a new robust volatility matrix estimator,with very mild assumptions on the cross-sectional dependence and tail behaviors of the noises,and demonstrated that it can achieve the optimal convergence rate n-1/4.Furthermore,the proposed model offered better explanatory and predictive powers by decomposing the estimator into low-rank and sparse components,using an appropriate regularization procedure.Simulation studies demonstrated that the proposed estimator outperforms its competitors under various dependence structures of microstructure noise.Additionally,an extensive analysis of the high-frequency data for stocks in the Shenzhen Stock Exchange of China demonstrated the practical effectiveness of the estimator.

关键词： Cross-sectional dependence high-dimensional data high-frequency data integrated volatility matrix market microstructure noise

Novel modelling strategies for high‑frequency stock trading data

在线全文

学校读者我要写书评

暂无评论

Financial Innovation 2023年第1期9卷 1030-1054页

作者： Xuekui Zhang Yuying Huang Ke Xu Li Xing Mathematics and statistics department at University of Victoria VictoriaCanada statistics and Actuarial Scienceat University of Waterloo WaterlooCanada Economics department at University of Victoria VictoriaCanada Mathematics and statistics department at University of Saskatchewan SaskatchewanCanada

Full electronic automation in stock exchanges has recently become popular,generat-ing high-frequency intraday data and motivating the development of near real-time price forecasting methods.Machine learning algorithms are widely applied to mid-price stock predictions.Processing raw data as inputs for prediction models(e.g.,data thinning and feature engineering)can primarily affect the performance of the prediction methods.However,researchers rarely discuss this topic.This motivated us to propose three novel modelling strategies for processing raw data.We illustrate how our novel modelling strategies improve forecasting performance by analyzing high-frequency data of the Dow Jones 30 component stocks.In these experiments,our strategies often lead to statistically significant improvement in predictions.The three strategies improve the F1 scores of the SVM models by 0.056,0.087,and 0.016,respectively.

关键词： High-frequency trading Machine learning Mid-price prediction strategy Raw data processing Multi-class prediction Ensemble learning

Fast algorithms for singular value decomposition and the inverse of nearly low-rank matrices

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

National Science Review 2023年第6期10卷 24-27页

作者： Chen Xu Weiwei Xu Kaili Jing department of Mathematics and statistics University of Ottawa School of Mathematics and statistics Xi'an Jiao Tong University School of Mathematics and statistics Nanjing University of Information Science and Technology

PROBLEM Matrix computation is a fundamental task in science and engineering;it is recognized as one of the seven computational’giants’of massive data analysis [1],analogous to the seven’dwarfs’in highperformance computing.In recent years,as the scale of datasets rapidly grows,analysts and engineers frequently need to deal with big matrices with a nearly lowrank structure.The big size of a matrix brings great numerical hurdles to matrix computation.In this work,we focus on two typical tasks in matrix computation:singular value decomposition (SVD) and matrix inverse on nearly low-rank matrices that are potentially of big sizes.

关键词：

Does Globalization, Tourism, Foreign Direct Investment, and Natural Resources Influencing Ecological Footprint?

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Urban and Environmental Studies 2022年第3期10卷 46-73页

作者： Tanzeela YAQOOB Maria BABI Rimsha KHALID Department of Statistics University of Karachi

The environmental problem has become a worldwide issue that must be frequently examined.Thus, this study investigates the relation of tourism, natural resources, globalization, and foreign direct investment on the ecological footprint of the USA, the UK, Pakistan, China, and India by using annual data from 1995 to 2020. The study applied Zivot and Andrews(1992) test to demonstrate the stationarity properties of the series, and an autoregressive distributed lag(ARDL)approach was employed to estimate the long-run and short-run dynamics. The long-run findings disclose that tourism has a significantly positive effect on China and Pakistan, but a significantly negative impact on India. The outcomes further suggest that foreign direct investment increases environmental degradation in India and China in both long and short periods, but contributes to improving the UK’s ecosystem. Besides, globalization in China tends to save its environment.Natural resources in the long run also harm the ecosystems of Pakistan, China, and the USA. The error correction term is negatively significant for all countries. The reliability of the model is investigated through diagnostic tests. The selected model is stable as the critical value of CUSUM and CUSUMSQ lie within the 5% significance level.

关键词： Ecological footprint tourism globalization environmental degradation natural resources

On Relations for Moments of Generalized Order statistics for Lindley–Weibull Distribution

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第4期41卷 197-208页

作者： Faten A.Momen khan Saman Hanif Shahbaz Muhammad Qaiser Shahbaz Department of Statistics University of JeddahJeddahKingdom of Saudi Arabia Department of Statistics King Abdulaziz UniversityJeddahKingdom of Saudi Arabia

Moments of generalized order statistics appear in several areas of science and engineering.These moments are useful in studying properties of the random variables which are arranged in increasing order of importance,for example,time to failure of a computer system.The computation of these moments is sometimes very tedious and hence some algorithms are required.One algorithm is to use a recursive method of computation of these moments and is very useful as it provides the basis to compute higher moments of generalized order statistics from the corresponding lower-order moments.Generalized order statistics pro-vides several models of ordered data as a special case.The moments of general-ized order statistics also provide moments of order statistics and record values as a special case.In this research,the recurrence relations for single,product,inverse and ratio moments of generalized order statistics will be obtained for Lindley–Weibull distribution.These relations will be helpful for obtained moments of gen-eralized order statistics from Lindley–Weibull distribution recursively.Special cases of the recurrence relations will also be obtained.Some characterizations of the distribution will also be obtained by using moments of generalized order statistics.These relations for moments and characterizations can be used in differ-ent areas of computer sciences where data is arranged in increasing order.

关键词： Generalized order statistics Lindley–Weibull distribution recurrence relations moments

Asymptotic in the Ordered Networks with a Noisy Degree Sequence

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2022年第3期35卷 1137-1153页

作者： LUO Jing QIN Hong department of Mathematics and statistics South-Central University for NationalitiesWuhan 430074China Department of Statistics Zhongnan University of Economics and LawWuhan 430073China

In the case of the differential privacy under the Laplace mechanism,the asymptotic properties of parameter estimators have been derived in some special network models with common binary values,but the asymptotic properties in network models with the ordered values are lacking.In this paper,the authors release the degree sequences of the ordered networks under a general noisy mechanism with the discrete Laplace mechanism as a special case.The authors establish the asymptotic result including the consistency and asymptotical normality of the parameter estimator when the number of parameters goes to infinity.Simulations and a real data example are provided to illustrate asymptotic results.

关键词： Asymptotic normality consistency degree differential privacy network data

Best Linear Unbiased Estimators of Location and Scale Ranked Set Parameters under Moving Extremes Sampling Design

在线全文

学校读者我要写书评

暂无评论

Acta Mathematicae Applicatae Sinica 2023年第2期39卷 222-231页

作者： Yan-fei DONG Wang-xue CHEN Min-yu XIE department of Mathematics and statistics Jishou UniversityJishou 416000China department of Mathematics and statistics Central China Normal UniversityWuhan 430079China

In the current paper,the best linear unbiased estimators(BLUEs)of location and scale parameters from location-scale family will be respectively proposed in cases when one parameter is known and when both are unknown under moving extremes ranked set sampling(MERSS).Explicit mathematical expressions of these estimators and their variances are derived.Their relative efficiencies with respect to the minimum variance unbiased estimators(MVUEs)under simple random sampling(SRS)are compared for the cases of some usual distributions.The numerical results show that the BLUEs under MERSS are significantly more efficient than the MVUEs under SRS.

关键词： location-scale parameters best linear unbiased estimator moving extremes ranked set sampling

A New Approach for Regression Analysis of Multivariate Current Status Data with Informative Censoring

在线全文

学校读者我要写书评

暂无评论

Communications in Mathematics and statistics 2023年第4期11卷 775-794页

作者： Huiqiong Li Chenchen Ma Jianguo Sun Niansheng Tang Department of Statistics Yunnan UniversityKunming 650091People’s Republic of China Department of Statistics University of MissouriColumbiaMO 65211USA

Regression analysis of interval-censored failure time data has recently attracted a great deal of attention partly due to their increasing occurrences in many fields.In this paper,we discuss a type of such data,multivariate current status data,where in addition to the complex interval data structure,one also faces dependent or informative censoring.For inference,a sieve maximum likelihood estimation procedure is developed and the proposed estimators of regression parameters are shown to be asymptotically consistent and efficient.For the implementation of the method,an EM algorithm is provided,and the results from an extensive simulation study demonstrate the validity and good performance of the proposed inference procedure.For an illustration,the proposed approach is applied to a tumorigenicity experiment.

关键词： Additive hazards model Current status data Informative censoring