Random Matrices-Theory and Applications最新文献_第10页

Efficient parameter estimation for multivariate accelerated failure time model via the quadratic inference functions method 基于二次推理函数的多变量加速失效时间模型的有效参数估计

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-10-23 DOI: 10.1142/S2010326319500138

L. Fu, Zhuoran Yang, Mingtao Zhao, Yan Zhou

引用次数: 0

Multiple change-points detection in high dimension 高维多变化点检测

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-10-23 DOI: 10.1142/S201032631950014X

Yunlong Wang, Changliang Zou, Zhaojun Wang, G. Yin

{"title":"Multiple change-points detection in high dimension","authors":"Yunlong Wang, Changliang Zou, Zhaojun Wang, G. Yin","doi":"10.1142/S201032631950014X","DOIUrl":"https://doi.org/10.1142/S201032631950014X","url":null,"abstract":"Change-point detection is an integral component of statistical modeling and estimation. For high-dimensional data, classical methods based on the Mahalanobis distance are typically inapplicable. We propose a novel testing statistic by combining a modified Euclidean distance and an extreme statistic, and its null distribution is asymptotically normal. The new method naturally strikes a balance between the detection abilities for both dense and sparse changes, which gives itself an edge to potentially outperform existing methods. Furthermore, the number of change-points is determined by a new Schwarz’s information criterion together with a pre-screening procedure, and the locations of the change-points can be estimated via the dynamic programming algorithm in conjunction with the intrinsic order structure of the objective function. Under some mild conditions, we show that the new method provides consistent estimation with an almost optimal rate. Simulation studies show that the proposed method has satisfactory performance of identifying multiple change-points in terms of power and estimation accuracy, and two real data examples are used for illustration.","PeriodicalId":54329,"journal":{"name":"Random Matrices-Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2019-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88141958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Author index Volume 8 (2019) 作者索引第8卷(2019)

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-10-01 DOI: 10.1142/s2010326319990016

引用次数: 0

Applications in random matrix theory of a PIII’ τ-function sequence from Okamoto’s Hamiltonian formulation 基于Okamoto哈密顿公式的PIII τ函数序列在随机矩阵理论中的应用

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-09-17 DOI: 10.1142/s2010326322500149

D. Dai, P. Forrester, Shuai‐Xia Xu

{"title":"Applications in random matrix theory of a PIII’ τ-function sequence from Okamoto’s Hamiltonian formulation","authors":"D. Dai, P. Forrester, Shuai‐Xia Xu","doi":"10.1142/s2010326322500149","DOIUrl":"https://doi.org/10.1142/s2010326322500149","url":null,"abstract":"We consider the singular linear statistic of the Laguerre unitary ensemble (LUE) consisting of the sum of the reciprocal of the eigenvalues. It is observed that the exponential generating function for this statistic can be written as a Toeplitz determinant with entries given in terms of particular [Formula: see text] Bessel functions. Earlier studies have identified the same determinant, but with the [Formula: see text] Bessel functions replaced by [Formula: see text] Bessel functions, as relating to the hard edge scaling limit of a generalized gap probability for the LUE, in the case of non-negative integer Laguerre parameter. We show that the Toeplitz determinant formed from an arbitrary linear combination of these two Bessel functions occurs as a [Formula: see text]-function sequence in Okamoto’s Hamiltonian formulation of Painlevé III[Formula: see text], and consequently the logarithmic derivative of both Toeplitz determinants satisfies the same [Formula: see text]-form Painlevé III[Formula: see text] differential equation, giving an explanation of a fact which can be observed from earlier results. In addition, some insights into the relationship between this characterization of the generating function, and its characterization in the [Formula: see text] limit, both with the Laguerre parameter [Formula: see text] fixed, and with [Formula: see text] (this latter circumstance being relevant to an application to the distribution of the Wigner time delay statistic), are given.","PeriodicalId":54329,"journal":{"name":"Random Matrices-Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84011628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Process convergence of fluctuations of linear eigenvalue statistics of random circulant matrices 随机循环矩阵线性特征值统计波动的过程收敛性

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-09-02 DOI: 10.1142/s2010326321500325

Shambhu Nath Maurya, Koushik Saha

引用次数: 7

Sampling distributions of optimal portfolio weights and characteristics in small and large dimensions 最优投资组合的小、大维度权重和特征的抽样分布

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-08-12 DOI: 10.1142/S2010326322500083

Taras Bodnar, H. Dette, Nestor Parolya, Erik Thorsén

{"title":"Sampling distributions of optimal portfolio weights and characteristics in small and large dimensions","authors":"Taras Bodnar, H. Dette, Nestor Parolya, Erik Thorsén","doi":"10.1142/S2010326322500083","DOIUrl":"https://doi.org/10.1142/S2010326322500083","url":null,"abstract":"Optimal portfolio selection problems are determined by the (unknown) parameters of the data generating process. If an investor wants to realize the position suggested by the optimal portfolios, he/she needs to estimate the unknown parameters and to account for the parameter uncertainty in the decision process. Most often, the parameters of interest are the population mean vector and the population covariance matrix of the asset return distribution. In this paper, we characterize the exact sampling distribution of the estimated optimal portfolio weights and their characteristics. This is done by deriving their sampling distribution by its stochastic representation. This approach possesses several advantages, e.g. (i) it determines the sampling distribution of the estimated optimal portfolio weights by expressions, which could be used to draw samples from this distribution efficiently; (ii) the application of the derived stochastic representation provides an easy way to obtain the asymptotic approximation of the sampling distribution. The later property is used to show that the high-dimensional asymptotic distribution of optimal portfolio weights is a multivariate normal and to determine its parameters. Moreover, a consistent estimator of optimal portfolio weights and their characteristics is derived under the high-dimensional settings. Via an extensive simulation study, we investigate the finite-sample performance of the derived asymptotic approximation and study its robustness to the violation of the model assumptions used in the derivation of the theoretical results.","PeriodicalId":54329,"journal":{"name":"Random Matrices-Theory and Applications","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2019-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87053006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Polynomial with cyclic monotone elements with applications to Random Matrices with discrete spectrum 循环单调元多项式及其在离散谱随机矩阵中的应用

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-08-01 DOI: 10.1142/s2010326321500209

Octavio Arizmendi, Adrian Celestino

引用次数: 4

Adjacency matrix comparison for stochastic block models 随机块模型的邻接矩阵比较

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-07-26 DOI: 10.1142/S2010326319500102

Guangren Yang, Songshan Yang, Wang Zhou

引用次数: 0

Boolean cumulants and subordination in free probability 自由概率中的布尔累积量与隶属关系

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-07-26 DOI: 10.1142/S2010326321500362

F. Lehner, K. Szpojankowski

引用次数: 2

Finite free convolutions via Weingarten calculus 通过Weingarten微积分得到的有限自由卷积

IF 0.9 4区数学

Random Matrices-Theory and Applications Pub Date : 2019-07-01 DOI: 10.1142/S2010326321500386

J. Campbell, Z. Yin

引用次数: 2