Selection of covariates is crucial in the estimation of average treatment effects given observational data with high or even ultra-high dimensional pretreatment variables. Existing methods for this problem typically a...
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We propose two simple regression models of Pearson correlation coefficient of two normal responses or binary responses to assess the effect of covariates of ***-based inference is established to estimate the regressio...
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We propose two simple regression models of Pearson correlation coefficient of two normal responses or binary responses to assess the effect of covariates of ***-based inference is established to estimate the regression coefficients,upon which bootstrap-based method is used to test the significance of covariates of *** studies show the effectiveness of the method in terms of type-I error control,power performance in moderate sample size and robustness with respect to model *** illustrate the application of the proposed method to some real data concerning health measurements.
Capital allocation is a core task in ffnancial reporting and risk management. This paper proposes two risk indicators, which can be applied to the ffeld of capital allocation modelling. We derive the optimal condition...
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In this paper, we study the problem of precision matrix estimation when the dataset contains sensitive information. In the differential privacy framework, we develop a differentially private ridge estimator by perturb...
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In this paper, we study the problem of precision matrix estimation when the dataset contains sensitive information. In the differential privacy framework, we develop a differentially private ridge estimator by perturbing the sample covariance matrix. Then we develop a differentially private graphical lasso estimator by using the alternating direction method of multipliers(ADMM) ***, we prove theoretical results showing that the differentially private ridge estimator for the precision matrix is consistent under fixed-dimension asymptotic, and establish a convergence rate of differentially private graphical lasso estimator in the Frobenius norm as both data dimension p and sample size n are allowed to grow. The empirical results that show the utility of the proposed methods are also provided.
MSC Codes 60C05, 60J10It is known that for the 2n-step symmetric simple random walk on , two events have the same probability if and only if their sets of paths have the same cardinality. In this article, we construct...
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This paper investigates the connection between neural networks and sufficient dimension reduction (SDR), demonstrating that neural networks inherently perform SDR in regression tasks under appropriate rank regularizat...
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In this paper, we systematically summarize and enhance the understanding of weak convergence and functional limits of record numbers in discrete-time random walks under Spitzer's condition, and extend these findin...
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We thank the editor,Professor Jun Shao,for orga-nizing this stimulating *** are grateful to all discussants for their insightful comments on our review article on the distributed statistical *** to the urgent need to ...
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We thank the editor,Professor Jun Shao,for orga-nizing this stimulating *** are grateful to all discussants for their insightful comments on our review article on the distributed statistical *** to the urgent need to process the datasets with massive sizes,various distributed computing methods have been proposed for the large-scale statistical ***,some important theoretical results were *** we want to give a relatively comprehensive overview on this hot topic,there are still some important works that have been missed in our review written over a year ***,we are glad to see the discussants provide reviews of some new works and *** hope that these discussions and our review would serve as a stimulus for further studies in this rapidly developing area.
We define a model for the joint distribution of multiple continuous latent variables which includes a model for how their correlations depend on explanatory variables. This is motivated by and applied to social scient...
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Multi-regional clinical trial (MRCT) has been common practice for drug development and global registration. The FDA guidance "Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Prod...
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