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Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference 使用中值推理的ARMA-GGARCH模型的零误差均值检验
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0013
Yaolan Ma, Mo Zhou, Liang Peng, Rongmao Zhang
{"title":"Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference","authors":"Yaolan Ma, Mo Zhou, Liang Peng, Rongmao Zhang","doi":"10.5705/ss.202022.0013","DOIUrl":"https://doi.org/10.5705/ss.202022.0013","url":null,"abstract":"Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference Abstract: The stylized fact of heavy tails makes median inferences appealing in fitting an ARMA model with heteroscedastic errors to financial returns. To ensure that the model still concerns the conditional mean, we test for a zero mean of the errors using a random weighted bootstrap method for quantifying estimation uncertainty. The proposed test is robust against heteroscedasticity and heavy tails as we do not infer the heteroscedasticity and need fewer finite moments. Simulations confirm the good finite sample performance in terms of size and power. Empirical applications caution the model interpretation after using a median inference.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
Robust Estimation of Covariance Matrices: Adversarial Contamination and Beyond 协方差矩阵的稳健估计:对抗污染及其他
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202021.0388
Stanislav Minsker, Lang Wang
{"title":"Robust Estimation of Covariance Matrices: Adversarial Contamination and Beyond","authors":"Stanislav Minsker, Lang Wang","doi":"10.5705/ss.202021.0388","DOIUrl":"https://doi.org/10.5705/ss.202021.0388","url":null,"abstract":"","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Scalable Estimation for High Velocity Survival Data Able to Accommodate Addition of Covariates 能够容纳协变量的高速生存数据的可扩展估计
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0028
Ying Sheng, Yifei Sun, C. E. Mcculloch, Chiung-Yu Huang
{"title":"Scalable Estimation for High Velocity Survival Data Able to Accommodate Addition of Covariates","authors":"Ying Sheng, Yifei Sun, C. E. Mcculloch, Chiung-Yu Huang","doi":"10.5705/ss.202022.0028","DOIUrl":"https://doi.org/10.5705/ss.202022.0028","url":null,"abstract":"Scalable Estimation for High Velocity Survival Data Able to Accommodate Addition of Covariates Abstract: With the rapidly increasing availability of large-scale streaming data, there has been a growing interest in developing methods that allow the processing of the data in batches without requiring storage of the full dataset. In this paper, we propose a hybrid likelihood approach for scalable estimation of the Cox model using individual-level data in the current data batch and summary statistics calculated from historical data. We show that the proposed scalable estimator is asymptotically as efficient as the maximum likelihood estimator calculated using the entire dataset with low data storage requirements and low loading and computation time. A challenge in analyzing survival data batches that is not accommodated in ex-tant methods is that new covariates may become available midway through data collection. To accommodate addition of covariates, we develop a hybrid empirical likelihood approach to incorporate the historical covariate effects evaluated in a reduced Cox model. The extended scalable estimator is asymptotically more efficient than the maximum likelihood estimator obtained using only the data batches that include the additional covariates. The proposed approaches are evaluated by numerical simulations and illustrated with an analysis of Surveillance, Epidemiology, and End Results breast data.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70938004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
On Estimation of the Logarithm of the Mean Squared Prediction Error of A Mixed-effect Predictor 混合效应预测器均方预测误差的对数估计
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0043
Jianling Wang, Thuan Nguyen, Y. Luan, Jiming Jiang
{"title":"On Estimation of the Logarithm of the Mean Squared Prediction Error of A Mixed-effect Predictor","authors":"Jianling Wang, Thuan Nguyen, Y. Luan, Jiming Jiang","doi":"10.5705/ss.202022.0043","DOIUrl":"https://doi.org/10.5705/ss.202022.0043","url":null,"abstract":": The mean squared prediction error (MSPE) is an important measure of uncertainty in small-area estimation. It is desirable to produce a second-order unbiased MSPE estimator, that is, the bias of the estimator is o ( m − 1 ), where m is the total number of small areas for which data are available. However, this is difficult, especially if the estimator needs to be positive, or at least nonnegative. In fact, very few MSPE estimators are both second-order unbiased and guaranteed to be positive. We consider an alternative, easier approach of estimating the logarithm of the MSPE (log-MSPE), thus avoiding the positivity problem. We derive a second-order unbiased estimator of the log-MSPE using the Prasad–Rao linearization method. The results of empirical studies demonstrate the superiority of the proposed log-MSPE estimator over a naive log-MSPE estimator and an existing method, known as McJack. Lastly, we demonstrate the proposed method by applying it to real data.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70938735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
Robust Rank Canonical Correlation Analysis for Multivariate Survival Data 多变量生存数据的稳健性秩典型相关分析
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0069
Di He, Yong Zhou, H. Zou
{"title":"Robust Rank Canonical Correlation Analysis for Multivariate Survival Data","authors":"Di He, Yong Zhou, H. Zou","doi":"10.5705/ss.202022.0069","DOIUrl":"https://doi.org/10.5705/ss.202022.0069","url":null,"abstract":"","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70938442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
On Combining Individual-Level Data With Summary Data in Statistical Inferences 论统计推断中个体数据与汇总数据的结合
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0228
Lu Deng, Sheng Fu, J. Qin, Kai Yu
{"title":"On Combining Individual-Level Data With Summary Data in Statistical Inferences","authors":"Lu Deng, Sheng Fu, J. Qin, Kai Yu","doi":"10.5705/ss.202022.0228","DOIUrl":"https://doi.org/10.5705/ss.202022.0228","url":null,"abstract":"On Combining Individual-Level Data With Summary Data in Statistical Inferences","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"34 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70939106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Asymptotic Behavior of the Maximum Likelihood Estimator for General Markov Switching Models 一般马尔可夫切换模型的极大似然估计量的渐近性
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202021.0336
C. Fuh, T. Pang
{"title":"Asymptotic Behavior of the Maximum Likelihood Estimator for General Markov Switching Models","authors":"C. Fuh, T. Pang","doi":"10.5705/ss.202021.0336","DOIUrl":"https://doi.org/10.5705/ss.202021.0336","url":null,"abstract":": Motivated by studying the asymptotic properties of the parameter estimator in switching linear state space models, switching GARCH models, switching stochastic volatility models, and recurrent neural networks, we investigate the maximum likelihood estimator for general Markov switching models. To this end, we first propose an innovative matrix-valued Markovian iterated function system (MIFS) representation for the likelihood function. Then, we express the derivatives of the MIFS as a composition of random matrices. To the best of our knowledge, this is a new method in the literature. Using this useful device, we establish the strong consistency and asymptotic normality of the maximum likelihood estimator under some regularity conditions. Furthermore, we characterize the Fisher information as the inverse of the asymptotic variance.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"23 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
A Perturbation Subsampling for Large Scale Data 大规模数据的扰动子抽样
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0020
Yujing Yao, Zhezhen Jin
{"title":"A Perturbation Subsampling for Large Scale Data","authors":"Yujing Yao, Zhezhen Jin","doi":"10.5705/ss.202022.0020","DOIUrl":"https://doi.org/10.5705/ss.202022.0020","url":null,"abstract":"Subsampling","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
An Adaptive Weighted Component Test for High-Dimensional Means 高维均值的自适应加权分量检验
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0143
Yidi Qu, L. Shu, Jinfeng Xu
{"title":"An Adaptive Weighted Component Test for High-Dimensional Means","authors":"Yidi Qu, L. Shu, Jinfeng Xu","doi":"10.5705/ss.202022.0143","DOIUrl":"https://doi.org/10.5705/ss.202022.0143","url":null,"abstract":"This supplementary materials provides detailed proofs of Theorem 1 and 2 and Proposition 1-3 as well as the power simulation results under the heteroscedastic condition.","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70938686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
Threshold Estimation in Proportional Mean Residual Life Model 比例平均剩余寿命模型的阈值估计
IF 1.4 3区 数学
Statistica Sinica Pub Date : 2024-01-01 DOI: 10.5705/ss.202022.0017
Bing Wang, Xinyuan Song
{"title":"Threshold Estimation in Proportional Mean Residual Life Model","authors":"Bing Wang, Xinyuan Song","doi":"10.5705/ss.202022.0017","DOIUrl":"https://doi.org/10.5705/ss.202022.0017","url":null,"abstract":"of the main","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70937929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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: 0
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