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Flexible Factor Model for Handling Missing Data in Supervised Learning

Communications in Mathematics and Statistics 2023年第2期11卷 477-501页

作者： Andriette Bekker Farzane Hashemi Mohammad Arashi Department of Statistics Faculty of Natural and Agricultural SciencesUniversity of PretoriaPretoriaSouth Africa Department of Statistics Faculty of Mathematical SciencesUniversity of KashanKashanIran Department of Statistics Faculty of Mathematical SciencesFerdowsi University of MashhadMashhadIran

This paper presents an extension of the factor analysis model based on the normal mean-variance mixture of the Birnbaum-Saunders in the presence of nonresponses and missing *** model can be used as a powerful tool to model non-normal features observed from data such as strongly skewed and heavy-tailed *** data may occur due to operator error or incomplete data capturing therefore cannot be ignored in factor analysis *** implement an EM-type algorithm for maximum likelihood estimation and propose single imputation of possible missing values under a missing at random *** potential and applicability of our proposed method are illustrated through analyzing both simulated and real datasets.

关键词： Automobile dataset Asymmetry ECME algorithm Factor analysis model heavy tails Incomplete data Liver disorders dataset

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The Finite Time Ruin Probability with the Same heavy-tailed Insurance and Financial Risks

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Acta Mathematicae Applicatae Sinica 2005年第1期21卷 153-156页

作者： Yi-qingChen Xiang-shengXie SchoolofEconomicsandManagement GuangdongUniversityofTechnologyGuangzhou510090China

This note complements a recent study in ruin theory with risky investment byestablishing the same asymptotic estimate for the finite time ruin probability under a weakerrestriction on the financial risks. In particular, our result applies to a critical case that theinsurance and financial risks have Pareto-type tails with the same regular index.

关键词： asymptotics heavy tails finite time ruin probability

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Bootstrap Test for Stationarity of heavy-Tailed Series with Structural Breaks

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Journal of Mathematical Research and Exposition 2010年第6期30卷 1015-1022页

作者： Rui Bing QIN Zheng TIAN Department of Applied Mathematics Northwestern Polytechnical UniversityShaanxi 710072P.R.China State Key Laboratory of Remote Sensing Science Beijing 100101P.R.China

The paper proposes a statistic to test stationarity of series with κ-stable innovations and structural breaks,obtains the asymptotical distribution of the statistic,and proves the consistency of the *** obtain critic values for the test without the estimation of the index κ,the paper proposes the bootstrap procedures to approximate the distribution,and proves the consistency of the *** simulations demonstrate that the bootstrap test is practical and powerful.

关键词： κ stable innovations structural breaks stationarity heavy tails bootstrap.

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Large Deviation on Random Sums for a Double Type-insurance Risk Model

Large Deviation on Random Sums for a Double Type-insurance R...

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2009 International Conference on Computational Intelligence and Natural Computing(CINC 2009)

作者： ZHAN Xiao-lin School of Science Shanghai Second Polytechnic University Shanghai China YU Li School of Science Hefei University of Technology Hefei China

A double-type-insurance risk model with heavy tails was defined and studied in ref. [1]. A further investigation into the large deviation on random sums under the distribution of dominated variation （D class） is pre... 详细信息

关键词： double type-insurance risk model heavy tails random sums large deviation dominated variation

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