High dimensional inference

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August undefined, 2024

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 Methods and Inference on Structural and Treatment Effects by Alexandre Belloni, Victor Chernozhukov and Christian Hansen. Published in volume 28, …

Lasso inference for high-dimensional time series - ScienceDirect

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 … WebIn the field of high-dimensional statistical inference more generally, uncertainty quantification has become a major theme over the last decade, originating with influential work on the debiased Lasso in (generalized) linear models (Javanmard and Montanari 2014; van de Geer et al. 2014; Zhang and Zhang 2014), and subsequently developed in other ... hidden shoulder clothes guard

High Dimensional Statistical Inference and Random Matrices

Web28 de out. de 2024 · This "high-dimensional regime" is reminiscent of statistical mechanics, which aims at describing the macroscopic behavior of a complex … WebAccess to Project Euclid content from this IP address has been suspended. If your organization is a subscriber, please contact your librarian/institutional administrator. If you are a non-subscriber, please contact the Help Desk. Business Office. 905 W. Main Street. Suite 18B. Durham, NC 27701 USA. WebHigh-Dimensional Methods and Inference on Structural and Treatment Effects by Alexandre Belloni, Victor Chernozhukov and Christian Hansen. Published in volume 28, issue 2, pages 29-50 of Journal of Economic Perspectives, Spring 2014, Abstract: Data with a large number of variables relative to the sa... hidden shores yuma resort map

Estimation and Inference for High Dimensional Factor Model …

Inference for high-dimensional varying-coefficient quantile …

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 … 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 penalized doubly robust method to estimate the optimal individualized treatment rule from high-dimensional data. hidden shower spy cameras for saleWebHowever, 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 … hidden showdown avatars

"Web15 de mai. de 2024 · Abstract: This paper presents a new approach, called perturb-max, for high-dimensional statistical inference in graphical models that is based on applying random perturbations followed by optimization. This framework injects randomness into maximum a-posteriori (MAP) predictors by randomly perturbing the potential function for … " - High dimensional inference

High dimensional inference

Statistical Inference for High-Dimensional Matrix-Variate Factor …

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 … WebIn statistical theory, the field of high-dimensional statistics studies data whose dimension is larger than typically considered in classical multivariate analysis.The area arose owing …

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WebCommunication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score. Fengrui Di, Fengrui Di. School of Statistics ... we focus on the distributed estimation and inference for a preconceived low-dimensional parameter vector in the high-dimensional quantile regression model with small ... Web7 de out. de 2024 · ABSTRACT. This article considers the estimation and inference of the low-rank components in high-dimensional matrix-variate factor models, where each …

WebIn the field of high-dimensional statistical inference more generally, uncertainty quantification has become a major theme over the last decade, originating with influential … Web1 de jan. de 2024 · High-dimensional linear models with independent errors have been well-studied. However, statistical inference on a high-dimensional linear model with heteroskedastic, dependent (and possibly ...

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, … Web19 de nov. de 2006 · High Dimensional Statistical Inference and Random Matrices. Iain M. Johnstone. Multivariate statistical analysis is concerned with observations on several …

Web12 de abr. de 2024 · A novel algorithm, TransHDGLM, that integrates data from the target study and the source studies is proposed. Minimax rate of convergence for estimation is established and the proposed estimator is shown to be rate-optimal. Statistical inference for the target regression coefficients is also studied.

Web28 de set. de 2024 · A common complication that can arise with analyses of high-dimensional data is the repeated use of hypothesis tests. A second complication, … hidden shower camera for saleWeb9 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 … hidden shower camper vanWebhigh-dimensional statistical theory, emphasizing a number of open problems. Key words and phrases: Inference, likelihood, model uncertainty, nuisance parameters, parameter orthogonalization, sparsity. 1. INTRODUCTION In broad terms, probability may be needed to describe a context in the initial planning phases of an investigation, hidden shores yumaWeb22 de jun. de 2024 · Download a PDF of the paper titled Inference in High-dimensional Linear Regression, by Heather S. Battey and Nancy Reid Download PDF Abstract: This … hidden shower curtain ideasWeb15 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 … hidden shrine near rito villageWeb20 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 … hidden shower drainsWebWe consider high-dimensional inference when the assumed linear model is misspecified. We describe some correct interpretations and corresponding sufficient assumptions for … hidden shower curtain