Increases in sea surface temperature (SST) and its variability (SSTV) in the context of climate change have a great impact on marine phytoplankton productivity, but their combined effects on phytoplankton biomass, esp...
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As the number and complexity of constraints in constrained multi-objective optimization problems (CMOPs) increase, the performance of existing constrained multi-objective evolutionary algorithms (CmoeAs) declines sign...
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In this paper, we focus on a class of time-inconsistent stochastic control problems, where the objective function includes the mean and several higher-order central moments of the terminal value of state. To tackle th...
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Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular *** exploration of how the genomes orchestrate the formation and maintenance of each cell,and control the...
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Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular *** exploration of how the genomes orchestrate the formation and maintenance of each cell,and control the cellular phenotypes of various organismsis,is both captivating and *** the inception of the first single-cell RNA technology,technologies related to single-cell sequencing have experienced rapid advancements in recent *** technologies have expanded horizontally to include single-cell genome,epigenome,proteome,and metabolome,while vertically,they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR ***-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases,including ***,we comprehensively summarize recent advances in single-cell omics technologies,with a specific focus on the methodology *** overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
In this paper,we analyze the relationship between the equilibrium reinsurance strategy and the tail of the distribution of the *** Mean Residual Life(MRL)has a close relationship with the tail of the distribution,we c...
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In this paper,we analyze the relationship between the equilibrium reinsurance strategy and the tail of the distribution of the *** Mean Residual Life(MRL)has a close relationship with the tail of the distribution,we consider two classes of risk distributions,Decreasing Mean Residual Life(DMRL)and Increasing Mean Residual Life(IMRL)distributions,which can be used to classify light-tailed and heavy-tailed distributions,*** assume that the underlying risk process is modelled by the classical CramérLundberg model *** the mean-variance criterion,by solving the extended Hamilton-Jacobi-Bellman equation,we derive the equilibrium reinsurance strategy for the insurer and the reinsurer under DMRL and IMRL,***,we analyze how to choose the reinsurance premium to make the insurer and the reinsurer agree with the same reinsurance *** find that under the case of DMRL,if the distribution and the risk aversions satisfy certain conditions,the insurer and the reinsurer can adopt a reinsurance premium to agree on a reinsurance strategy,and under the case of IMRL,the insurer and the reinsurer can only agree with each other that the insurer do not purchase the reinsurance.
Motivated by a medical study that attempts to analyze the relationship between growth curves and other variables and to measure the association among multiple growth curves,the authors develop a functional multiple-ou...
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Motivated by a medical study that attempts to analyze the relationship between growth curves and other variables and to measure the association among multiple growth curves,the authors develop a functional multiple-outcome model to decompose the total variation of multiple functional outcomes into variation explained by independent variables with time-varying coefficient functions,by latent factors and by *** latent factors are the hidden common factors that influence the multiple outcomes and are found through the combined functional principal component analysis *** the coefficients of the latent factors one may further explore the association of the multiple *** method is applied to the multivariate growth data of infants in a real medical study in Shanghai and produces interpretable *** rates for the proposed estimates of the varying coefficient and covariance functions of the model are derived under mild conditions.
The problem of hazard rate estimation under right-censored assumption has been investigated *** square error(ISE)of estimation is one of the most widely accepted measurements of the global performance for nonparametri...
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The problem of hazard rate estimation under right-censored assumption has been investigated *** square error(ISE)of estimation is one of the most widely accepted measurements of the global performance for nonparametric kernel *** there are no results available for ISE of hazard rate estimation under right-censored model with censoring indicators missing at random(MAR)so *** paper constructs an imputation estimator of the hazard rate function and establish asymptotic normality of the ISE for the kernel hazard rate estimator with censoring indicators *** the same time,an asymptotic representation of the mean integrated square error(MISE)is also *** finite sample behavior of the estimator is investigated via one simple simulation.
The authors propose a two-step test for the two-sample problem of processes of OrnsteinUhlenbeck type. In the first step, the authors test the equality of correlation structures, based on the least square estimators o...
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The authors propose a two-step test for the two-sample problem of processes of OrnsteinUhlenbeck type. In the first step, the authors test the equality of correlation structures, based on the least square estimators of the correlation parameters, and the test statistic follows the standard normal distribution. If the null hypothesis is not rejected in the first step, the authors consider a second step to test the equality of marginal distributions, based on the weighted deviation of the empirical characteristic functions;the test statistic has a complicated asymptotic distribution, so that sequential bootstrap method is applied to reach a temporary decision. Simulation studies and real data analysis suggest that the proposed approach performs well in finite samples.
Published auxiliary information can be helpful in conducting statistical inference in a new *** this paper,we synthesize the auxiliary information with semiparametric likelihood-based inference for censoring data with...
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Published auxiliary information can be helpful in conducting statistical inference in a new *** this paper,we synthesize the auxiliary information with semiparametric likelihood-based inference for censoring data with the total sample size is *** express the auxiliary information as constraints on the regression coefficients and the covariate distribution,then use empirical likelihood method for general estimating equations to improve the efficiency of the interested parameters in the specified *** consistency and asymptotic normality of the resulting regression parameter estimators *** numerical simulation and application with different supposed conditions show that the proposed method yields a substantial gain in efficiency of the interested parameters.
High-dimensional data streams are ubiquitous in modern manufacturing, due to their ability to provide valuable information about the industrial system’s performance on a real-time basis. If a shift occurs in a produc...
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High-dimensional data streams are ubiquitous in modern manufacturing, due to their ability to provide valuable information about the industrial system’s performance on a real-time basis. If a shift occurs in a production process, fault diagnosis based on the data streams is of critical importance for identifying the root cause. Existing methods have largely focused on controlling the total missed discovery rate without distinguishing missed signals for positive versus negative components of the shift vector. In practice, however, losses incurred from the two directional shifts can differ substantially, so it is desirable to constrain the proportions of missed signals for positive and negative components at two distinctive levels. In this article, we propose a fault classification procedure that controls the two proportions separately. By formulating the problem as Lagrangian multiplier optimization, we show that the proposed procedure is optimal in the sense that it minimizes the expected number of false discoveries. We also suggest an iterative adjustment algorithm that converges to the optimal Lagrangian parameters. The asymptotic optimality for the data-driven version of our procedure is also established. Theoretical justification and numerical comparison with state-of-the-art methods show that the proposed procedure works well in applications.
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