High dimensional inference
Webhigh-dimensional statistical theory, emphasizing a number of open problems. Key words and phrases: Inference, likelihood, model uncertainty, nuisance parameters, parameter … 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 dimension of the matrix-variates (p × q) is comparable to or greater than the number of observations (T).We propose an estimation method called α-PCA that preserves the …
High dimensional inference
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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, … 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 …
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 … 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.
Webhigh-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, WebIn this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time …
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, …
WebTo the best of our knowledge, no structural inference methods exist for sparse high-dimensional systems. Our paper attempts to fill this gap. By now, a quite large literature has emerged that deals with the problem of fitting sparse high-dimensional VAR models using ℓ 1 -penalized estimators; see among others Song and Bickel (2011), Han et al. … grandfather in little miss sunshineWebAbstract Linear regression models with stationary errors are well studied but the non-stationary assumption is more realistic in practice. An estimation and inference procedure for high-dimensional... grandfather in polishWeb9 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 … chinese checkers wall gameWebCommunication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score. Fengrui Di, Fengrui Di. School of Statistics ... we … grandfather in ojibweWebHigh-Dimensional Methods and Inference on Structural and Treatment Effects† Alexandre Belloni is Associate Professor of Decision Sciences, Fuqua School of Business, Duke … grandfather in portugueseWebIn the field of high-dimensional statistical inference more generally, uncertainty quantification has become a major theme over the last decade, originating with influential … grandfather in polish spellingWebCommunication-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 ... chinese checkers name origin