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Anisotropic extensions of isotropic Finch–Skea metric in the charged modified gravity

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Communications in Theoretical Physics 2024年第9期76卷 120-142页

作者： Tayyab Naseer M Sharif department of Mathematics and statistics The University of Lahore

In this study, we explore the Finch–Skea perfect fluid solution and extend its domain to three distinct anisotropic interior models within the framework of the f(R, T) theory, incorporating the influence of an electromagnetic field. We assume a static spherical spacetime initially coupled with an isotropic matter distribution. We then introduce a Lagrangian corresponding to an additional gravitating source, taking into account its role in inducing pressure anisotropy within the original fluid source. By deriving the field equations for the combined matter setup, we applied a radial component transformation, which yielded two distinct systems of equations. In addition, we consider a charged exterior spacetime to determine the three constants associated with the Finch–Skea solution at the boundary. Our findings suggest that under certain parametric choices, all three resulting models exhibited physical relevance within this modified theory.

关键词： anisotropy gravitational decoupling modified gravity

Character Sheaves for Classical Graded Lie Algebras

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Acta Mathematica Sinica,English Series 2024年第3期40卷 870-884页

作者： Ting XUE School of Mathematics and statistics University of MelbourneVIC 3010Australia department of Mathematics and statistics University of HelsinkiHelsinki 00014Finland

In this note we study character sheaves for graded Lie algebras arising from inner automorphisms of special linear groups and Vinberg’s type Ⅱ classical graded Lie algebras.

关键词： Graded Lie algebras character sheaves Fourier transform nilpotent orbits

Berry-Esseen bounds for self-normalized sums of locally dependent random variables

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Science China Mathematics 2024年第11期67卷 2629-2652页

作者： Zhuo-Song Zhang department of statistics and Data Science Southern University of Science and Technology

The Berry-Esseen bound provides an upper bound on the Kolmogorov distance between a random variable and the normal *** this paper,we establish Berry-Esseen bounds with optimal rates for self-normalized sums of locally dependent random variables,assuming only a second-moment *** proof leverages Stein's method and introduces a novel randomized concentration inequality,which may also be of independent interest for other *** main results have applied to self-normalized sums of m-dependent random variables and graph dependency models.

关键词： Berry-Esseen bounds self-normalized sums localdependence $m$-dependence graph dependency

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Double Moving Extremes Ranked Set Sampling Design

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 75-90页

作者： Meng Chen Wang-xue Chen Rui Yang department of Mathematics and statistics Jishou UniversityJishou416000China

The traditional simple random sampling(SRS)design method is inefficient in many *** proposed some new designs to increase *** this paper,as a variation of moving extremes ranked set sampling(MERSS),double MERSS(DMERSS)is proposed and its properties for estimating the population mean are *** turns out that,when the underlying distribution is symmetric,DMERSS gives unbiased estimators of the population ***,it is found that DMERSS is more efficient than the SRS and MERSS methods for usual symmetric distributions(normal and uniform).For asymmetric distributions considered in this study,the DMERSS has a small bias and it is more efficient than SRS for usual asymmetric distribution(exponential)for small sample sizes.

关键词： double moving extremes ranked set sampling symmetric distribution efficiency

Asymptotics for the joint tail probability of bidimensional randomly weighted sums with applications to insurance

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Science China Mathematics 2024年第1期67卷 163-186页

作者： Yang Yang Shaoying Chen Kam Chuen Yuen School of statistics and Data Science Nanjing Audit UniversityNanjing 211815China department of statistics and Actuarial Science The University of Hong KongHong Kong 999077China

This paper studies the joint tail behavior of two randomly weighted sums∑_(i=1)^(m)Θ_(i)X_(i)and∑_(j=1)^(n)θ_(j)Y_(j)for some m,n∈N∪{∞},in which the primary random variables{X_(i);i∈N}and{Y_(i);i∈N},respectively,are real-valued,dependent and heavy-tailed,while the random weights{Θi,θi;i∈N}are nonnegative and arbitrarily dependent,but the three sequences{X_(i);i∈N},{Y_(i);i∈N}and{Θ_(i),θ_(i);i∈N}are mutually *** two types of weak dependence assumptions on the heavy-tailed primary random variables and some mild moment conditions on the random weights,we establish some(uniformly)asymptotic formulas for the joint tail probability of the two randomly weighted sums,expressing the insensitivity with respect to the underlying weak dependence *** applications,we consider both discrete-time and continuous-time insurance risk models,and obtain some asymptotic results for ruin probabilities.

关键词： asymptotic joint tail behavior randomly weighted sum heavy-tailed distribution dependence insurance risk model

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Sequential good lattice point sets for computer experiments

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Science China Mathematics 2024年第9期67卷 2153-2170页

作者： Xue-Ru Zhang Yong-Dao Zhou Min-Qian Liu Dennis K.J.Lin NITFID LPMC&KLMDASRSchool of Statistics and Data ScienceNankai UniversityTianjin 300071China department of statistics Purdue UniversityWest LafayetteIN 47907USA

Sequential Latin hypercube designs(SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are inflexible, and algorithmic methods are ineffective for large designs. For designs in contracting spaces, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing SLHDs via good lattice point sets in various experimental spaces. These designs are called sequential good lattice point(SGLP) sets. Moreover, we provide efficient approaches for identifying the(nearly)optimal SGLP sets under a given criterion. Combining the linear level permutation technique, we obtain a class of asymptotically optimal SLHDs in invariant spaces, where the L1-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the SGLP set has a better space-filling property than the existing SLHDs in invariant spaces. It is also shown that SGLP sets have less computational complexity and more adaptability.

关键词： contracting space maximin distance nested Latin hypercube design sequential design space-fillingdesign

Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

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Computers, Materials & Continua 2024年第3期78卷 3529-3549页

作者： Ying Su Morgan C.Wang Shuai Liu department of statistics and Data Science University of Central FloridaOrlandoFL32816-2370USA School of Mathematics and statistics Beijing Technology and Business UniversityBeijing100048China

Long-term time series forecasting stands as a crucial research domain within the realm of automated machine learning(AutoML).At present,forecasting,whether rooted in machine learning or statistical learning,typically relies on expert input and necessitates substantial manual *** manual effort spans model development,feature engineering,hyper-parameter tuning,and the intricate construction of time series *** complexity of these tasks renders complete automation unfeasible,as they inherently demand human intervention at multiple *** surmount these challenges,this article proposes leveraging Long Short-Term Memory,which is the variant of Recurrent Neural Networks,harnessing memory cells and gating mechanisms to facilitate long-term time series ***,forecasting accuracy by particular neural network and traditional models can degrade significantly,when addressing long-term time-series ***,our research demonstrates that this innovative approach outperforms the traditional Autoregressive Integrated Moving Average(ARIMA)method in forecasting long-term univariate time *** is a high-quality and competitive model in time series prediction,and yet it requires significant preprocessing *** multiple accuracy metrics,we have evaluated both ARIMA and proposed method on the simulated time-series data and real data in both short and long ***,our findings indicate its superiority over alternative network architectures,including Fully Connected Neural Networks,Convolutional Neural Networks,and Nonpooling Convolutional Neural *** AutoML approach enables non-professional to attain highly accurate and effective time series forecasting,and can be widely applied to various domains,particularly in business and finance.

关键词： Automated machine learning autoregressive integrated moving average neural networks time series analysis

Optimal Control of Service Rates of Discrete-Time(s,Q)Queueing-Inventory Systems with Finite Buffer

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 261-280页

作者： L.Iniya B.Sivakumar G.Arivarignan School of Mathematics Madurai Kamaraj UniversityMaduraiTamilnaduIndia department of statistics Manonmaniam Sundaranar UniversityTirunelveliTamilnaduIndia

This article,we develop an optimal policy to control the service rate of a discrete time queueing-inventory system with finite *** customers arrive according to a Bernoulli process and the service time for the customers are *** the buffer size attains its maximum,any arriving new customers are considered to be *** customers are served one by one according to FCFS rule and each customers request random number of *** inventory is replenished according to a(s,Q)inventory policy with geometric lead *** main objectives of this article are to determine the service rates to be employed at each slot so that the long run expected cost rate is minimized for fixed inventory level and fixed buffer size and to minimize the expected waiting time for a fixed inventory level and fixed buffer *** problems are modelled as Markov decision *** establish the existence of a stationary policy and employ linear programming method to find the optimal service *** provide some numerical examples to illustrate the behaviour of the model.

关键词： Queueing-inventory system discrete time batch demand-Markov decision process

A fiducial approach to the nonparametric deconvolution problem:The discrete case

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Science China Mathematics 2024年第11期67卷 2653-2670页

作者： Yifan Cui Jan Hannig Center for Data Science Zhejiang University department of statistics and Operations Research University of North Carolina at Chapel Hill

Fiducial inference is applied to nonparametric g-modeling in the discrete *** propose a computationally efficient algorithm to sample from the fiducial distribution and use the generated samples to construct point estimates and confidence *** study the theoretical properties of the fiducial distribution and perform extensive simulations in various *** proposed approach gives rise to good statistical performance in terms of the mean squared error of point estimators and coverage of confidence ***,we apply the proposed fiducial method to estimate the probability of each satellite site being malignant using gastric adenocarcinoma data with 844 patients.

关键词： confidence intervals empirical Bayes fiducial inference nonparametric deconvolution

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