High-dimensional statistical inference
WebSpringer Nature 2024 LATEX template Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models T. Tony Cai1, Zijian Guo2 and Yin Xia3 1Department of Statistics ... WebIn statistical theory, the field of high-dimensional statistics studies data whose dimension is larger than typically considered in classical multivariate analysis.The area …
High-dimensional statistical inference
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Web31 de dez. de 2024 · This Special Issue solicit submissions in, but not limited to, the following areas: Applications based on statistical inference from high dimensional data; Dimensionality reduction with imbalanced biological datasets; Applications based on feature selection (e.g., text processing, bioinformatics, medical informatics and natural language ... WebEstimation and inference of change points in high-dimensional factor models. Journal of Econometrics 219, 66-100. [4] Bai, J., Li, K., 2012. Statistical analysis of factor models of high dimension. Annals of Statistics 40, 436-465. [5] Bai, J., Li, K., 2016. Maximum likelihood estimation and inference for approximate factor models of high ...
Web9 de fev. de 2015 · A new inferential framework for constructing confidence regions and testing hypotheses in statistical models specified by a system of high dimensional estimating equations is proposed, which is likelihood-free and provides valid inference for a broad class of highdimensional constrained estimating equation problems, which are … WebDownloadable (with restrictions)! Confidence sets are of key importance in high-dimensional statistical inference. Under case–control study, a popular response-selective sampling design in medical study or econometrics, we consider the confidence intervals and statistical tests for single or low-dimensional parameters in high-dimensional logistic …
Web2.2.1 Optimality of statistical inference In high-dimensional linear model, the paper [31] established the minimax expected length of the con dence interval over the parameter … WebIn this work, we study high-dimensional varying-coefficient quantile regression models and develop new tools for statistical inference. We focus on development of valid confidence intervals and honest tests for nonparametric coefficients at a fixed time point and quantile, while allowing for a high-dimensional setting where the number of input ...
WebHigh-Dimensional Statistical Inferences Ming Yuan, Columbia University Scribe: Kiran Vodrahalli 01/22/2024 1 LECTURE 1: Introduction I will focus on the methods, theory, …
WebHigh-dimensional statistics focuses on data sets in which the number of features is of comparable size, or larger than the number of observations. Data sets of this type present a variety of new challenges, since classical theory and methodology can break down in surprising and unexpected ways. Researchers at Berkeley study both the statistical ... siat strapping toolsWeb10 de ago. de 2024 · In this paper we develop an online statistical inference approach for high-dimensional generalized linear models with streaming data for real-time estimation … the people most at risk for malnutrition are:WebDepartment of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, P.R. China. Correspondence to: Yu Chen, Department of … the people most at risk for malnutrition areWebfor Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. the people minerWeb5 de abr. de 2024 · For high-dimensional statistical inference, de-sparsifying methods have received popularity thanks to their appealing asymptotic properties. Existing results … siat telycoWeb29 de ago. de 2016 · Here, we reformulate high-dimensional statistical inference in the framework of the statistical physics of quenched disorder to address these fundamental issues for big data. We are accordingly able to obtain powerful generalizations of time-honored classical statistical theorems dating back to the 1940s. the people movementWebEstimation and inference of change points in high-dimensional factor models. Journal of Econometrics 219, 66-100. [4] Bai, J., Li, K., 2012. Statistical analysis of factor models … siat tocantins