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学者姓名：吴密霞
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Abstract ：
Variance changepoints in economics, finance, biomedicine, oceanography, etc. are frequent and significant. To better detect these changepoints, we propose a new technique for constructing confidence intervals for the variances of a noisy sequence with multiple changepoints by combining bootstrapping with the weighted sequential binary segmentation (WSBS) algorithm and the Bayesian information criterion (BIC). The intensity score obtained from the bootstrap replications is introduced to reflect the possibility that each location is, or is close to, one of the changepoints. On this basis, a new changepoint estimation is proposed, and its asymptotic properties are derived. The simulated results show that the proposed method has superior performance in comparison with the state-of-the-art segmentation methods. Finally, the method is applied to weekly stock prices, oceanographic data, DNA copy number data and traffic flow data.
Keyword ：
WSBS algorithm WSBS algorithm weighted bootstrap weighted bootstrap Variance changepoint Variance changepoint BIC BIC confidence interval confidence interval
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| GB/T 7714 | Li, Yang , Yan, Qijing , Wu, Mixia et al. Bootstrap-based inference for multiple variance changepoint models [J]. | JOURNAL OF APPLIED STATISTICS , 2025 . |
| MLA | Li, Yang et al. "Bootstrap-based inference for multiple variance changepoint models" . | JOURNAL OF APPLIED STATISTICS (2025) . |
| APA | Li, Yang , Yan, Qijing , Wu, Mixia , Liu, Aiyi . Bootstrap-based inference for multiple variance changepoint models . | JOURNAL OF APPLIED STATISTICS , 2025 . |
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Abstract ：
In this paper, bias-corrected instrumental variable estimation methods, specifically the bias- corrected two-stage least square (2SLS) estimation and the bias-corrected asymptotically best 2SLS estimation, are proposed for spatial autoregressive (SAR) models with covariate measurement errors, utilizing available information regarding the variance of the measurement error. Under mild assumptions, the consistency and asymptotic normality of the proposed estimators are derived. Simulation studies further reveal that the proposed methods exhibit robustness regardless of the presence of spatial dependence in the model. Additionally, a real data example is utilized to illustrate the developed methods.
Keyword ：
Bias-corrected Bias-corrected Measurement error Measurement error Instrumental variable Instrumental variable Spatial data Spatial data
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| GB/T 7714 | Luo, Guowang , Wu, Mixia . Bias-corrected instrumental variable estimation for spatial autoregressive models with measurement errors [J]. | SPATIAL STATISTICS , 2025 , 65 . |
| MLA | Luo, Guowang et al. "Bias-corrected instrumental variable estimation for spatial autoregressive models with measurement errors" . | SPATIAL STATISTICS 65 (2025) . |
| APA | Luo, Guowang , Wu, Mixia . Bias-corrected instrumental variable estimation for spatial autoregressive models with measurement errors . | SPATIAL STATISTICS , 2025 , 65 . |
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Abstract ：
The Expectation Maximization (EM) algorithm is widely used in latent variable model inference. However, when data are distributed across various locations, directly applying the EM algorithm can often be impractical due to communication expenses and privacy considerations. To address these challenges, a communication-efficient distributed EM algorithm is proposed. Under mild conditions, the proposed estimator achieves the same mean squared error bound as the centralized estimator. Furthermore, the proposed method requires only one extra round of communication compared to the Average estimator. Numerical simulations and a real data example demonstrate that the proposed estimator significantly outperforms the Average estimator in terms of mean squared errors.
Keyword ：
Latent variable models Latent variable models EM algorithm EM algorithm Distributed inference Distributed inference Communication-efficient Communication-efficient
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| GB/T 7714 | Liu, Xirui , Wu, Mixia , Xu, Liwen . Communication-efficient distributed EM algorithm [J]. | STATISTICAL PAPERS , 2024 , 65 (9) : 5575-5592 . |
| MLA | Liu, Xirui et al. "Communication-efficient distributed EM algorithm" . | STATISTICAL PAPERS 65 . 9 (2024) : 5575-5592 . |
| APA | Liu, Xirui , Wu, Mixia , Xu, Liwen . Communication-efficient distributed EM algorithm . | STATISTICAL PAPERS , 2024 , 65 (9) , 5575-5592 . |
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Abstract ：
In this paper, we consider the distributed inference for heterogeneous linear models with massive datasets. Noting that heterogeneity may exist not only in the expectations of the subpopulations, but also in their variances, we propose the heteroscedasticity-adaptive distributed aggregation (HADA) estimation, which is shown to be communication-efficient and asymptotically optimal, regardless of homoscedasticity or heteroscedasticity. Furthermore, a distributed test for parameter heterogeneity across subpopulations is constructed based on the HADA estimator. The finite-sample performance of the proposed methods is evaluated using simulation studies and the NYC flight data.
Keyword ：
Levene's test Levene's test massive heterogeneous data massive heterogeneous data Distributed estimation Distributed estimation heterogeneity heterogeneity
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| GB/T 7714 | Yang, Xin , Yan, Qi Jing , Wu, Mi Xia . Adaptive Distributed Inference for Multi-source Massive Heterogeneous Data [J]. | ACTA MATHEMATICA SINICA-ENGLISH SERIES , 2024 , 40 (11) : 2751-2770 . |
| MLA | Yang, Xin et al. "Adaptive Distributed Inference for Multi-source Massive Heterogeneous Data" . | ACTA MATHEMATICA SINICA-ENGLISH SERIES 40 . 11 (2024) : 2751-2770 . |
| APA | Yang, Xin , Yan, Qi Jing , Wu, Mi Xia . Adaptive Distributed Inference for Multi-source Massive Heterogeneous Data . | ACTA MATHEMATICA SINICA-ENGLISH SERIES , 2024 , 40 (11) , 2751-2770 . |
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Abstract ：
Identifying multiple change points in the mean and/or variance is crucial across various fields, including finance and quality control. We introduce a novel technique that detects change points for the mean and/or variance of a noisy sequence and constructs confidence intervals for both the mean and variance of the sequence. This method integrates the weighted bootstrap with the Sequential Binary Segmentation (SBS) algorithm. Not only does our technique pinpoint the location and number of change points, but it also determines the type of change for each estimated point, specifying whether the change occurred in the mean, variance, or both. Our simulations show that our method outperforms other approaches in most scenarios, clearly demonstrating its superiority. Finally, we apply our technique to three datasets, including DNA copy number variation, stock volume, and traffic flow data, further validating its practical utility and wide-ranging applicability.
Keyword ：
Mean-variance change points Mean-variance change points the SBS algorithm the SBS algorithm the intensity score the intensity score confidence interval confidence interval the weighted bootstrap the weighted bootstrap
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| GB/T 7714 | Li, Yang , Wu, Mixia , Ding, Wenxin . Bootstrap-based inference for multiple mean-variance changepoint models [J]. | JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION , 2024 , 95 (1) : 70-95 . |
| MLA | Li, Yang et al. "Bootstrap-based inference for multiple mean-variance changepoint models" . | JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 95 . 1 (2024) : 70-95 . |
| APA | Li, Yang , Wu, Mixia , Ding, Wenxin . Bootstrap-based inference for multiple mean-variance changepoint models . | JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION , 2024 , 95 (1) , 70-95 . |
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Abstract ：
本文研究了响应变量随机缺失时部分线性空间自回归模型的估计问题.结合B样条方法,我们给出了该模型参数部分和非数部分的极大似然估计的EM算法、伪限制极大似然估计的EM算法、以及边际极大似然估计算法,并通过数值模拟比较了三种估计和相应算法在不同的样本容量、缺失比例及空间权重矩阵下数值表现.最后,通过一个实际例子进一步验证三种方法的优良性.
Keyword ：
EM算法 EM算法 缺失数据 缺失数据 空间自回归 空间自回归 似然方法 似然方法 样条逼近 样条逼近
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| GB/T 7714 | 马万霞 , 吴密霞 , 罗国旺 . 缺失数据下半参数空间自回归模型的估计 [J]. | 数学学报 , 2023 , 66 (6) : 1031-1044 . |
| MLA | 马万霞 et al. "缺失数据下半参数空间自回归模型的估计" . | 数学学报 66 . 6 (2023) : 1031-1044 . |
| APA | 马万霞 , 吴密霞 , 罗国旺 . 缺失数据下半参数空间自回归模型的估计 . | 数学学报 , 2023 , 66 (6) , 1031-1044 . |
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Abstract ：
The rank-tracking probability (RTP) is a useful statistical index for measuring the 'tracking ability' of longitudinal disease risk factors in biomedical studies. Two existing unstructured smoothing methods for estimating the RTP in literature require sufficient observations at any two design time points, which may be violated in practice. We consider the dynamic estimation methods based on semiparametric copula modeling and smoothing method and compare the corresponding estimators under three smoothing ways: parametric-smoothing (C-PAS), probability-smoothing (C-PRS) and RTP-smoothing (C-RS). The proposed estimators are consistent under some mild assumptions when the true copula model is known. Among them, the C-PAS, though performs best under the true copula model, is not robust for the copula model selection. The C-PRS and C-RS estimators are preferred under the selected copula model, which have much smaller mean squared errors than unstructured smoothing methods. Moreover, the C-RS estimator performs slightly better than C-PRS estimator. Some numerical simulations and an application of a longitudinal epidemiological study are carried out to illustrate the performances of the proposed methods.
Keyword ：
two-step smoothing two-step smoothing semiparametric copulal semiparametric copulal kernel smoothing kernel smoothing rank-tracking probability rank-tracking probability
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| GB/T 7714 | Zhang, Xiaoyu , Wu, Mixia , Wu, Colin O. . Dynamic copula-based methods for estimating rank-tracking probabilities with longitudinal data [J]. | STAT , 2023 , 12 (1) . |
| MLA | Zhang, Xiaoyu et al. "Dynamic copula-based methods for estimating rank-tracking probabilities with longitudinal data" . | STAT 12 . 1 (2023) . |
| APA | Zhang, Xiaoyu , Wu, Mixia , Wu, Colin O. . Dynamic copula-based methods for estimating rank-tracking probabilities with longitudinal data . | STAT , 2023 , 12 (1) . |
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Abstract ：
本文考虑多源异质大数据下线性模型的分布式统计推断问题.首先,提出针对模型参数的通信有效的分布式聚合估计及算法,并在一些正则条件下证明所得到的估计量的最优性和渐近正态性.其次,针对模型中的异质性检验问题,给出了分布式检验方法.最后,通过数值模拟研究,对本文所提出估计和检验方法的优良性进行验证.
Keyword ：
分布式统计推断 分布式统计推断 多源数据 多源数据 大数据 大数据 异质性 异质性 线性模型 线性模型
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| GB/T 7714 | 杨鑫 , 吴密霞 . 多源异质大数据线性模型的分布式统计推断 [J]. | 数学学报 , 2023 , 66 (2) : 263-276 . |
| MLA | 杨鑫 et al. "多源异质大数据线性模型的分布式统计推断" . | 数学学报 66 . 2 (2023) : 263-276 . |
| APA | 杨鑫 , 吴密霞 . 多源异质大数据线性模型的分布式统计推断 . | 数学学报 , 2023 , 66 (2) , 263-276 . |
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Abstract ：
Receiver operating characteristic (ROC) curve is a popular tool to describe and compare the diagnostic accuracy of biomarkers when a binary-scale gold standard is available. However, there are many examples of diagnostic tests whose gold standards are continuous. Hence, Several extensions of receiver operating characteristic (ROC) curve are proposed to evaluate the diagnostic potential of biomarkers when the gold standard is continuous-scale. Moreover, in evaluating these biomarkers, it is often necessary to consider the effects of covariates on the diagnostic accuracy of the biomarker of interest. Covariates may include subject characteristics, expertise of the test operator, test procedures or aspects of specimen handling. Applying the covariate adjustment to the case that the gold standard is continuous is challenging and has not been addressed in the literature. To fill the gap, we propose two general testing frameworks to account for the covariates effect on diagnostic accuracy. Simulation studies are conducted to compare the proposed tests. Data from a study that assessed three types of imaging modalities with the purpose of detecting neoplastic colon polyps and cancers are used to illustrate the proposed methods.
Keyword ：
diagnostic accuracy diagnostic accuracy biomarkers biomarkers covariate adjustment covariate adjustment regression analysis regression analysis
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| GB/T 7714 | Wu, Mixia , Sun, Xian , Liu, Aiyi et al. Significance tests for covariates in the diagnostic accuracy index of a biomarker against a continuous gold standard [J]. | STATISTICS IN MEDICINE , 2023 , 42 (22) : 4015-4027 . |
| MLA | Wu, Mixia et al. "Significance tests for covariates in the diagnostic accuracy index of a biomarker against a continuous gold standard" . | STATISTICS IN MEDICINE 42 . 22 (2023) : 4015-4027 . |
| APA | Wu, Mixia , Sun, Xian , Liu, Aiyi , Peng, Chenchen , Li, Zhaohai . Significance tests for covariates in the diagnostic accuracy index of a biomarker against a continuous gold standard . | STATISTICS IN MEDICINE , 2023 , 42 (22) , 4015-4027 . |
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Abstract ：
本文研究了响应变量随机缺失时部分线性空间自回归模型的估计问题.结合B样条方法,我们给出了该模型参数部分和非数部分的极大似然估计的EM算法、伪限制极大似然估计的EM算法、以及边际极大似然估计算法,并通过数值模拟比较了三种估计和相应算法在不同的样本容量、缺失比例及空间权重矩阵下数值表现.最后,通过一个实际例子进一步验证三种方法的优良性.
Keyword ：
EM算法 EM算法 空间自回归 空间自回归 样条逼近 样条逼近 缺失数据 缺失数据 似然方法 似然方法
Cite：
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| GB/T 7714 | 马万霞 , 吴密霞 , 罗国旺 . 缺失数据下半参数空间自回归模型的估计 [J]. | 数学学报(中文版) , 2023 , 66 (06) : 1031-1044 . |
| MLA | 马万霞 et al. "缺失数据下半参数空间自回归模型的估计" . | 数学学报(中文版) 66 . 06 (2023) : 1031-1044 . |
| APA | 马万霞 , 吴密霞 , 罗国旺 . 缺失数据下半参数空间自回归模型的估计 . | 数学学报(中文版) , 2023 , 66 (06) , 1031-1044 . |
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