Some perspectives on inference in high dimensions
type: Item
instance of: scholarly article
title: Some perspectives on inference in high dimensions
DOI: 10.1214/21-STS824
author: Heather Battey
author: D. R. Cox
published in: Statistical Science
publication date: 2022-02-16T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 7474200
zbMATH Keywords: inference
zbMATH Keywords: likelihood
zbMATH Keywords: model uncertainty
zbMATH Keywords: nuisance parameters
zbMATH Keywords: parameter orthogonalization
zbMATH Keywords: sparsity
MaRDI profile type: Publication
cites work: Bounds for the asymptotic distribution of the likelihood ratio
cites work: On a formula for the distribution of the maximum likelihood estimator
cites work: Q3339093
cites work: Parametric statistical models and likelihood
cites work: Q4280419
cites work: Q4326424
cites work: Large numbers of explanatory variables: a probabilistic assessment
cites work: High dimensional nuisance parameters: an example from parametric survival analysis
cites work: Valid post-selection inference
cites work: Some Systematic Supersaturated Designs
cites work: Models as approximations. I. Consequences illustrated with linear regression
cites work: Confidence intervals for high-dimensional linear regression: minimax rates and adaptivity
cites work: Double/debiased machine learning for treatment and structural parameters
cites work: Q5654899
cites work: Partial likelihood
cites work: A note on data-splitting for the evaluation of significance levels
cites work: Large numbers of explanatory variables, a semi-descriptive analysis
cites work: Q4725475
cites work: The theory of the design of experiments
cites work: Q3996151
cites work: Q3125701
cites work: Comment: Models are approximations!
cites work: Q5381132
cites work: Testing and Confidence Intervals for High Dimensional Proportional Hazards Models
cites work: Q4849049
cites work: Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
cites work: Exact post-selection inference, with application to the Lasso
cites work: Asymptotics for high dimensional regression \(M\)-estimates: fixed design results
cites work: Using empirical partially Bayes inference for increased efficiency
cites work: Q3816821
cites work: A significance test for the lasso
cites work: Statistical sparsity
cites work: A general theory of hypothesis tests and confidence regions for sparse high dimensional models
cites work: A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores
cites work: Q3237829
cites work: A modern maximum-likelihood theory for high-dimensional logistic regression
cites work: Modified Likelihood root in High Dimensions
cites work: Selective inference with a randomized response
cites work: Q4864293
cites work: On asymptotically optimal confidence regions and tests for high-dimensional models
cites work: High-Dimensional Probability
cites work: Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
full work available at URL: 21-sts824
OpenAlex ID: W4205738559
description: scientific article; zbMATH DE number 7474200