杨虎教授 - 统计与精算 - SCI论坛

被SSCI检索的论文列表：（统计截止时间2022.5.5）

WLAD-LASSO method for robust estimation and variable selection in partially linear models

Yang, H and Li, N

2018 | COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 47 (20) , pp.4958-4976

This paper focuses on robust estimation and variable selection for partially linear models. We combine the weighted least absolute deviation (WLAD) regression with the adaptive least absolute shrinkage and selection operator (LASSO) to achieve simultaneous robust estimation and variable selection for partially linear models. Compared with the LAD-LASSO method, the WLAD-LASSO method will resist

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Penalized and constrained LAD estimation in fixed and high dimension

Wu, XF; Liang, RM and Yang, H

Feb 2022 | Mar 2021 (在线发表) | STATISTICAL PAPERS 63 (1) , pp.53-95

Recently, many literatures have proved that prior information and structure in many application fields can be formulated as constraints on regression coefficients. Following these work, we propose a L-1 penalized LAD estimation with some linear constraints in this paper. Different from constrained lasso, our estimation performs well when heavy-tailed errors or outliers are found in the response

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On a discrete risk model with two-sided jumps

Yang, H and Zhang, ZM

Jun 1 2010 | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 234 (3) , pp.835-844

In this paper, we consider a discrete renewal risk model with phase-type interarrival times and two-sided jumps. In this model, downward jumps represent claim loss, while upward jumps are also allowed to represent random gains. Assume that the downward jumps have an arbitrary probability function and the upward jumps have a rational probability generating function. We study the (Gerber-Shiu) di

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RUIN PROBABILITY IN A SEMI-MARKOV RISK MODEL WITH CONSTANT INTEREST FORCE AND HEAVY-TAILED CLAIMS

Yang, H and Xue, K

Jul 2013 | ACTA MATHEMATICA SCIENTIA 33 (4) , pp.998-1006

In the present paper, we consider a kind of semi-Markov risk model (SMRM) with constant interest force and heavy-tailed claims, in which the claim rates and sizes are conditionally independent, both fluctuating according to the state of the risk business. First, we derive a matrix integro-differential equation satisfied by the survival probabilities. Second, we analyze the asymptotic behaviors

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Preliminary test Liu estimators based on the conflicting W, LR and LM tests in a regression model with multivariate Student-t error

Yang, H and Xu, JW

May 2011 | METRIKA 73 (3) , pp.275-292

In this paper, the problem of estimation of the regression coefficients in a multiple regression model with multivariate Student-t error is considered under the multicollinearity situation when it is suspected that the regression coefficients may be restricted to a linear manifold. The preliminary test Liu estimators (PTLE) based on the Wald, Likelihood ratio (LR) and Lagrangian multiplier (LM)

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Gerber-Shiu analysis in a perturbed risk model with dependence between claim sizes and interclaim times

Zhang, ZM and Yang, H

Jan 1 2011 | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 235 (5) , pp.1189-1204

In this paper, we consider a compound Poisson risk model perturbed by a Brownian motion. We construct the bivariate cumulative distribution function of the claim size and interclaim time by Farlie-Gumbel-Morgenstern copula. The integro-differential equations and the Laplace transforms for the Gerber-Shiu functions are obtained. We also show that the Gerber-Shiu functions satisfy some defective

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Ruin problems in a discrete Markov risk model

Yang, H; Zhang, ZM and Lan, CM

Jan 1 2009 | STATISTICS & PROBABILITY LETTERS 79 (1) , pp.21-28

In this paper, we extend the compound binomial risk model to a Markov dependent model in which the claim occurrence and the claim amount are both regulated by a discrete time Markov process. The explicit expression for the "discounted" joint probability function of the surplus before ruin and the deficit at ruin is derived when the initial surplus u = 0, and a recursive formula to calculate suc

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Gerber-Shiu discounted penalty function in a Sparre Andersen model with multi-layer dividend strategy

Yang, H and Zhang, ZM

Jun 2008 | INSURANCE MATHEMATICS & ECONOMICS 42 (3) , pp.984-991

This paper studies a Sparre Andersen model in which the inter-claim times are generalized Erlang(n) distributed. We assume that the premium rate is a step function depending on the current surplus level. A piecewise integro-differential equation for the Gerber-Shiu discounted penalty function is derived and solved. Finally, to illustrate the solution procedure, explicit expression for the Lapla

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A generalized penalty function in the Sparre-Andersen risk model with two-sided jumps

Zhang, ZM and Yang, H

Apr 1 2010 | STATISTICS & PROBABILITY LETTERS 80 (7-8) , pp.597-607

In this paper, we consider a Sparre-Andersen risk model with two-sided jumps, where the downward jumps represent the claims as usual and the upward jumps are also allowed to explain random gains. A generalized discounted penalty function is studied by using random walk techniques and the renewal theory. (C) 2009 Elsevier B.V. All rights reserved.

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On a perturbed Sparre Andersen risk model with multi-layer dividend strategy

Yang, H and Zhang, ZM

Oct 15 2009 | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 232 (2) , pp.612-624

In this paper, we consider a perturbed Sparre Andersen risk model, in which the inter-claim times are generalized Erlang(n) distributed. Under the multi-layer dividend strategy, piece-wise integro-differential equations for the discounted penalty functions are derived, and a recursive approach is applied to express the solutions. A numerical example to calculate the ruin probabilities is given

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On a risk model with stochastic premiums income and dependence between income and loss

Zhang, ZM and Yang, H

May 1 2010 | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 234 (1) , pp.44-57

Labbe and Sendova (2009) [9] consider a compound Poisson risk model with stochastic premiums income. In this paper, we extend their model by assuming that there exists a specific dependence structure among the claim sizes, interclaim times and premium sizes. Assume that the distributions of the premium sizes and interclaim times are controlled by the claim sizes. When the individual premium siz

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On a class of renewal risk model with random income

Yang, H and Zhang, ZM

Nov-dec 2009 | APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY 25 (6) , pp.678-695

In this paper, we consider a renewal risk process with random premium income based on a Poisson process. Generating function for the discounted penalty function is obtained. We show that the discounted penalty function satisfies a defective renewal equation and the corresponding explicit expression can be obtained via a compound geometric tail. Finally, we consider the Laplace transform of the

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The perturbed compound Poisson risk model with multi-layer dividend strategy

Yang, H and Zhang, ZM

Jan 1 2009 | STATISTICS & PROBABILITY LETTERS 79 (1) , pp.70-78

In this paper, we consider a perturbed compound Poisson risk model with multi-layer dividend strategy. Integro-differential and integral equations for the expected discounted penalty function are derived and solved. When the claims are subexponentially distributed, the asymptotic formula for ruin probability is obtained. (c) 2008 Elsevier B.V. All rights reserved.

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On a compound Poisson risk model with delayed claims and random incomes

Hao, YY and Yang, H

Aug 15 2011 | APPLIED MATHEMATICS AND COMPUTATION 217 (24) , pp.10195-10204

The main focus of this paper is to analyze the Gerber-Shiu penalty function of a compound Poisson risk model with delayed claims and random incomes. It is assumed that every main claim will produce a by-claim which can be delayed with a certain probability. We derive the integral equation satisfied by the Gerber-Shiu penalty function. Given that the premium size is exponentially distributed, th

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Semiparametric EGARCH model with the case study of China stock market

Yang, H and Wu, XC

May 2011 | ECONOMIC MODELLING 28 (3) , pp.761-766

In this paper, we propose a new semiparametric method for GARCH model by combining the EGARCH (1,1) model and local polynomial regression. Based on the idea of two-stage estimate, a link function is estimated by the local polynomial and then the parameters are obtained via the weighted least square method. Finally we apply this method to the Shanghai Composite Index in the China stock market an

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A kind of new time-weighted nonnegative lasso index-tracking model and its application

Chen, QA; Hu, QY; (...); Qi, K

Jan 2022 | Dec 2021 (在线发表) | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 59

This study describes improved index-tracking methods to replicate the target index's market performance in a high-dimensional sparse linear regression with nonnegative constraints on the coefficients. The main objective of this study is to construct a sparse portfolio with a better prediction effect and robustness. Considering the influence of time factors on index tracking, we propose a time-w

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On a Sparre Andersen risk model perturbed by a spectrally negative Levy process

Zhang, ZM; Yang, HL and Yang, H

May 1 2013 | SCANDINAVIAN ACTUARIAL JOURNAL (3) , pp.213-239

In this paper, we consider a Sparre Andersen risk model perturbed by a spectrally negative Levy process (SNLP). Assuming that the interclaim times follow a Coxian distribution, we show that the Laplace transforms and defective renewal equations for the GerberShiu functions can be obtained by employing the roots of a generalized Lundberg equation. When the SNLP is a combination of a Brownian mot

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On a nonparametric estimator for ruin probability in the classical risk model

Zhang, ZM; Yang, HL and Yang, H

Jun 1 2014 | SCANDINAVIAN ACTUARIAL JOURNAL 2014 (4) , pp.309-338

In this paper, we present a nonparametric estimator for ruin probability in the classical risk model with unknown claim size distribution. We construct the estimator by Fourier inversion and kernel density estimation method. Under some conditions imposed on the kernel, bandwidth and claim size density, we present some large sample properties of the estimator. Some simulation studies are also gi

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On a Sparre Andersen Risk Model with Time-Dependent Claim Sizes and Jump-Diffusion Perturbation

Zhang, ZM; Yang, HL and Yang, H

Dec 2012 | METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY 14 (4) , pp.973-995

In this paper, we consider a Sparre Andersen risk model where the interclaim time and claim size follow some bivariate distribution. Assuming that the risk model is also perturbed by a jump-diffusion process, we study the Gerber-Shiu functions when ruin is due to a claim or the jump-diffusion process. By using a q-potential measure, we obtain some integral equations for the Gerber-Shiu function

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Penalized LAD Regression for Single-index Models

Yang, H; Lv, J and Guo, CH

1st Meeting of y-BIS / 1st Meeting of jSPE

2016 | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 45 (7) , pp.2392-2408

In this article, we consider the penalized LAD regression which deals with variable selection and estimation simultaneously for single-index models. The proposed estimator is robust and efficient with respect to heavy tailed errors or outliers in the response. Then, we introduce a practical algorithm where the unknown link function is estimated by local linear smoothing combined with LAD regres

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Nonnegative estimation and variable selection via adaptive elastic-net for high-dimensional data

Li, N; Yang, H and Yang, J

Dec 2 2021 | Jul 2019 (在线发表) | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 50 (12) , pp.4263-4279

This paper proposes the nonnegative adaptive elastic-net for simultaneous nonnegative estimation and variable selection in sparse high-dimensional linear regression models. By inheriting the good features of adaptive elastic-net, the nonnegative adaptive elastic-net enjoys the oracle property even in high-dimensional settings where the dimension of covariates can be much larger than the sample

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Conditioning theory of the equality constrained quadratic programming and its applications

Wang, SX and Yang, H

Apr 26 2021 | May 2019 (在线发表) | LINEAR & MULTILINEAR ALGEBRA 69 (6) , pp.1161-1183

Perturbation analysis of the equality constrained quadratic programming is considered. We present two different perturbation bounds to explore underlying factors for affecting the conditioning of equality constrained quadratic programming, and propose the condition numbers to give sharp forward error bounds. To improve the computational efficiency of condition numbers, some new compact forms an

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On the penalized maximum likelihood estimation of high-dimensional approximate factor model

Wang, SX; Yang, H and Yao, CL

Jun 2019 | COMPUTATIONAL STATISTICS 34 (2) , pp.819-846

In this paper, we mainly focus on the penalized maximum likelihood estimation of the high-dimensional approximate factor model. Since the current estimation procedure can not guarantee the positive definiteness of the error covariance matrix, by reformulating the estimation of error covariance matrix and based on the lagrangian duality, we propose an accelerated proximal gradient (APG) algorith

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The perturbed compound Poisson risk model with two-sided jumps

Zhang, ZM; Yang, H and Li, SM

Feb 15 2010 | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 233 (8) , pp.1773-1784

In this paper, we consider a perturbed compound Poisson risk model with two-sided jumps. The downward jumps represent the claims following an arbitrary distribution, while the upward jumps are also allowed to represent the random gains. Assuming that the density function of the upward jumps has a rational Laplace transform, the Laplace transforms and defective renewal equations for the discount

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Rank-based shrinkage estimation for identification in semiparametric additive models

Yang, J; Yang, H and Lu, F

Aug 2019 | STATISTICAL PAPERS 60 (4) , pp.1255-1281

In this paper, we propose a novel and robust procedure for model identification in semiparametric additive models based on rank regression and spline approximation. Under some mild conditions, we establish the theoretical properties of the identified nonparametric functions and the linear parameters. Furthermore, we demonstrate that the proposed rank estimate has a great efficiency gain across

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