Electronic Journal of Statistics最新文献_第3页

Sieve estimation of semiparametric accelerated mean models with panel count data 具有面板计数数据的半参数加速平均模型的筛估计

IF 1.1 4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2128

Xiangbin Hu, Wen Su, Xingqiu Zhao

引用次数: 0

Nonregular designs from Paley’s Hadamard matrices: Generalized resolution, projectivity and hidden projection property 来自Paley Hadamard矩阵的不规则设计:广义分辨率、投影性和隐投影性质

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2148

Guanzhou Chen, Chenlu Shi, Boxin Tang

引用次数: 0

Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression 高斯过程回归中稀疏谱变分近似的不确定性量化

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2155

Dennis Nieman, Botond Szabo, Harry van Zanten

引用次数: 2

Regression analysis of mixed sparse synchronous and asynchronous longitudinal covariates with varying-coefficient models 混合稀疏同步与异步纵向协变量的变系数模型回归分析

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2175

Congmin Liu, Zhuowei Sun, Hongyuan Cao

{"title":"Regression analysis of mixed sparse synchronous and asynchronous longitudinal covariates with varying-coefficient models","authors":"Congmin Liu, Zhuowei Sun, Hongyuan Cao","doi":"10.1214/23-ejs2175","DOIUrl":"https://doi.org/10.1214/23-ejs2175","url":null,"abstract":"We consider varying-coefficient models for mixed synchronous and asynchronous longitudinal covariates, where asynchronicity refers to the misalignment of longitudinal measurement times within an individual. We propose three different methods of parameter estimation and inference. The first method is a one-step approach that estimates non-parametric regression functions for synchronous and asynchronous longitudinal covariates simultaneously. The second method is a two-step approach in which synchronous longitudinal covariates are regressed with the longitudinal response by centering the synchronous longitudinal covariates first and, in the second step, the residuals from the first step are regressed with asynchronous longitudinal covariates. The third method is the same as the second method except that in the first step, we omit the asynchronous longitudinal covariate and include a non-parametric intercept in the regression analysis of synchronous longitudinal covariates and the longitudinal response. We further construct simultaneous confidence bands for the non-parametric regression functions to quantify the overall magnitude of variation. Extensive simulation studies provide numerical support for the theoretical findings. The practical utility of the methods is illustrated on a dataset from the ADNI study.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135662402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Towards optimal doubly robust estimation of heterogeneous causal effects 对异质性因果效应的最优双稳健估计

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2157

Edward H. Kennedy

{"title":"Towards optimal doubly robust estimation of heterogeneous causal effects","authors":"Edward H. Kennedy","doi":"10.1214/23-ejs2157","DOIUrl":"https://doi.org/10.1214/23-ejs2157","url":null,"abstract":"Heterogeneous effect estimation is crucial in causal inference, with applications across medicine and social science. Many methods for estimating conditional average treatment effects (CATEs) have been proposed, but there are gaps in understanding if and when such methods are optimal. This is especially true when the CATE has nontrivial structure (e.g., smoothness or sparsity). Our work contributes in several ways. First, we study a two-stage doubly robust CATE estimator and give a generic error bound, which yields rates faster than much of the literature. We apply the bound to derive error rates in smooth nonparametric models, and give sufficient conditions for oracle efficiency. Along the way we give a general error bound for regression with estimated outcomes; this is the second main contribution. The third contribution is aimed at understanding the fundamental statistical limits of CATE estimation. To that end, we propose and study a local polynomial adaptation of double-residual regression. We show that this estimator can be oracle efficient under even weaker conditions, and we conjecture that they are minimal in a minimax sense. We go on to give error bounds in the non-trivial regime where oracle rates cannot be achieved. Some finite-sample properties are explored with simulations.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135662404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 194

Asymptotic normality of a change plane estimator in fixed dimension with near-optimal rate 具有近最优速率的固定维变换平面估计量的渐近正态性

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2144

Debarghya Mukherjee, Moulinath Banerjee, Debasri Mukherjee, Ya’acov Ritov

{"title":"Asymptotic normality of a change plane estimator in fixed dimension with near-optimal rate","authors":"Debarghya Mukherjee, Moulinath Banerjee, Debasri Mukherjee, Ya’acov Ritov","doi":"10.1214/23-ejs2144","DOIUrl":"https://doi.org/10.1214/23-ejs2144","url":null,"abstract":"Linear thresholding models postulate that the conditional distribution of a response variable in terms of covariates differs on the two sides of a (typically unknown) hyperplane in the covariate space. A key goal in such models is to learn about this separating hyperplane. Exact likelihood or least squares methods to estimate the thresholding parameter involve an indicator function which make them difficult to optimize and are, therefore, often tackled by using a surrogate loss that uses a smooth approximation to the indicator. In this paper, we demonstrate that the resulting estimator is asymptotically normal with a near optimal rate of convergence: n−1 up to a log factor, in both classification and regression thresholding models. This is substantially faster than the currently established convergence rates of smoothed estimators for similar models in the statistics and econometrics literatures. We also present a real-data application of our approach to an environmental data set where CO2 emission is explained in terms of a separating hyperplane defined through per-capita GDP and urban agglomeration.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135954678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Testing linear operator constraints in functional response regression with incomplete response functions 不完全响应函数在函数响应回归中的线性算子约束检验

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2177

Yeonjoo Park, Kyunghee Han, Douglas G. Simpson

{"title":"Testing linear operator constraints in functional response regression with incomplete response functions","authors":"Yeonjoo Park, Kyunghee Han, Douglas G. Simpson","doi":"10.1214/23-ejs2177","DOIUrl":"https://doi.org/10.1214/23-ejs2177","url":null,"abstract":"Hypothesis testing procedures are developed to assess linear operator constraints in function-on-scalar regression when incomplete functional responses are observed. The approach enables statistical inferences about the shape and other aspects of the functional regression coefficients within a unified framework encompassing three incomplete sampling scenarios; (i) partially observed response functions as curve segments over random sub-intervals of the domain, (ii) discretely observed functional responses with additive measurement errors, and (iii) the composition of former two scenarios, where partially observed response segments are observed discretely with measurement error. The latter scenario has been little explored to date, although such structured data is increasingly common in applications. For statistical inference, deviations from the constraint space are measured via integrated L2-distance between estimates from the constrained and unconstrained model spaces. Large sample properties of the proposed test procedure are established, including the consistency, asymptotic distribution, and local power of the test statistic. The finite sample power and level of the proposed test are investigated in a simulation study covering a variety of scenarios. The proposed methodologies are illustrated by applications to U.S. obesity prevalence data, analyzing the functional shape of its trends over time, and motion analysis in a study of automotive ergonomics.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135662403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Spectrum inference for replicated spatial locally time-harmonizable time series 复制空间局部时间可调和时间序列的谱推断

IF 1.1 4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2130

J. Aston, D. Dehay, A. Dudek, Jean-Marc Freyermuth, Dénes Szűcs, Lincoln J. Colling

引用次数: 0

Uniform confidence bands for hazard functions from censored prevalent cohort survival data 经审查的流行队列生存数据的危险函数的统一置信带

IF 1.1 4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2133

Ali Shariati, H. Doosti, V. Fakoor, M. Asgharian

引用次数: 0

Kernel machines with missing covariates 缺少协变量的核机

4区数学

Electronic Journal of Statistics Pub Date : 2023-01-01 DOI: 10.1214/23-ejs2158

Tiantian Liu, Yair Goldberg

引用次数: 0