High dimensional inference

Author: niwz

August undefined, 2024

WebSpringer Nature 2024 LATEX template Statistical Inference and Large-scale Multiple Testing for High-dimensional Regression Models T. Tony Cai1, Zijian Guo2 and Yin … Web1 de jan. de 2024 · For high-dimensional parametric models, estimation and hypothesis testing for mean and covariance matrices have been extensively studied. However, the practical implementation of these methods is fairly limited and is primarily restricted to …

Communication-efficient estimation and inference for high …

Web1 de jul. de 2024 · High-dimensional inference, on the other hand, is much less developed. In particular, although considerable progress has been made for inference in standard high-dimensional regression (Javanmard and Montanari, 2014, van de Geer et al., 2014, Zhang and Zhang, 2014, Ning and Liu, 2024), much less is known for more … 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 ... hif-1 alpha protein

Estimation and Inference for High-Dimensional Generalized …

Web15 de nov. de 2024 · In this paper we develop valid inference for high-dimensional time series. We extend the desparsified lasso to a time series setting under Near-Epoch Dependence (NED) assumptions allowing for non-Gaussian, serially correlated and heteroskedastic processes, where the number of regressors can possibly grow faster … Web14 de abr. de 2024 · Background: High-dimensional mediation analysis is an extension of unidimensional mediation analysis that includes multiple mediators, and increasingly it is being used to evaluate the indirect omics-layer effects of environmental exposures on health outcomes. Analyses involving high-dimensional mediators raise several statistical … Web14 de abr. de 2024 · Traditional Food Knowledge (TFK) is needed to define the acculturation of culture, society, and health in the context of food. TFK is essential for a … hif1an是什么

[2101.04491] Bayesian inference in high-dimensional models

High-dimensional empirical likelihood inference Biometrika

Web21 de dez. de 2024 · We develop theory of high-dimensional U-statistic, circumvent challenges stemming from the non-smoothness of loss function, and establish … WebHigh-Dimensional Methods and Inference on Structural and Treatment Effects by Alexandre Belloni, Victor Chernozhukov and Christian Hansen. Published in volume 28, … hif1anWebMoreover, the manifold hypothesis is widely applied in machine learning to approximate high-dimensional data using a small number of parameters . Experimental studies showed that a dynamical collapse occurs in the brain from incoherent baseline activity to low-dimensional coherent activity across neural nodes [ 66 – 68 ]. hif1 and hif2

"Web4 de jul. de 2024 · FACT: High-Dimensional Random Forests Inference. Random forests is one of the most widely used machine learning methods over the past decade thanks to its outstanding empirical performance. Yet, because of its black-box nature, the results by random forests can be hard to interpret in many big data applications. " - High dimensional inference

High dimensional inference

Estimation and Inference for High Dimensional Factor Model with …

Web19 de nov. de 2006 · High Dimensional Statistical Inference and Random Matrices. Iain M. Johnstone. Multivariate statistical analysis is concerned with observations on several variables which are thought to possess some degree of inter-dependence. Driven by problems in genetics and the social sciences, it first flowered in the earlier half of the last … WebHowever, there is a lack of valid inference procedures for such rules developed from this type of data in the presence of high-dimensional covariates. In this work, we develop a …

Did you know?

Web12 de jan. de 2024 · In this paper, we review these properties of Bayesian and related methods for several high-dimensional models such as many normal means problem, … WebBy dealing with strong and weak signals separately, our work combines sparse regression techniques with Stein estimation to build an honest and adaptive confidence set in high-dimensional regression. Corollaries 3 and 4 provide theoretical guarantees for the use of popular sparse regression methods, lasso and MCP, in our two-step method.

Web15 de nov. de 2024 · This dimensionality enhancement substantially improved therapeutic inference, significantly shifting the therapeutic function leftward to 56.0% (CI = 54.65–57.35%) ( Fig. 3 A, in red). As predicted, reanalysing the same data within a high-dimensional framework potentially enables us to detect the value of interventions that … Web20 de ago. de 2024 · With the availability of high-dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients’ survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes.

Web28 de out. de 2024 · This "high-dimensional regime" is reminiscent of statistical mechanics, which aims at describing the macroscopic behavior of a complex … 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 …

WebMulti-armed bandits in high-dimension More noise sensitivity to the choice of tuning parameter Linear UCB with variable selection attains oracle properties Issues of dynamic …

Web22 de out. de 2024 · First, we propose to construct a new set of estimating equations such that the impact from estimating the high-dimensional nuisance parameters becomes … how far is 1600 kilometers in milesWebMulti-armed bandits in high-dimension More noise sensitivity to the choice of tuning parameter Linear UCB with variable selection attains oracle properties Issues of dynamic variable selection in high-dimension Kosuke Imai (Princeton) High-Dimensional Causal Inference Harvard/MIT (Feb., 2016) 11 / 11 how far is 15 yards in feetWebCommunication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score. Fengrui Di, Fengrui Di. School of Statistics ... we … hif1a molecular weightWebHigh Dimensional Change Point Inference: Recent Developments and Extensions J Multivar Anal. 2024 Mar;188:104833. doi: 10.1016/j ... Based on that, we provide a survey of some extensions to general high dimensional parameters beyond mean vectors as well as strategies for testing multiple change points in high dimensions. hif1a pancreatic cancerWeb9 de out. de 2024 · In this work we will argue that the bootstrap is very useful for individual and especially for simultaneous inference in high-dimensional linear models, that is for testing individual or group hypotheses H_ {0,j} or H_ {0,G}, and for corresponding individual or simultaneous confidence regions. We thereby also demonstrate its usefulness to deal ... hif1a信号通路图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 ... how far is 15 meters in minecraftWeb9 de out. de 2024 · The authors should be congratulated on their insightful article proposing forms of residual and paired bootstrap methodologies in the context of simultaneous testing in sparse and high-dimensional linear models. We appreciate the clear exposition of their work, and the effectiveness of the proposed method. The authors advocate for the … how far is 15 stadia