The effects of a hypertension diagnosis on health behaviors: A two-dimensional regression discontinuity analysis.
Sign Up to like & getrecommendations! Published in 2022 at "Health economics"
DOI: 10.1002/hec.4466
Abstract: This paper explores how a diagnosis of hypertension might affect a person's health-related behaviors. The analysis uses a two-dimensional regression discontinuity design because hypertension is diagnosed when a person's systolic or diastolic blood pressure (SBP… read more here.
Keywords: dimensional regression; health; two dimensional; regression discontinuity ... See more keywords
Feature selection for high‐dimensional regression via sparse LSSVR based on Lp ‐norm
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22334
Abstract: When solving many regression problems, there exist a large number of input features. However, not all features are relevant for current regression, and sometimes, including irrelevant features may deteriorate the learning performance. Therefore, it is… read more here.
Keywords: high dimensional; feature selection; regression; lssvr ... See more keywords
Probabilistic partition of unity networks for high‐dimensional regression problems
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DOI: 10.1002/nme.7207
Abstract: We explore the probabilistic partition of unity network (PPOU‐Net) model in the context of high‐dimensional regression problems and propose a general framework focusing on adaptive dimensionality reduction. With the proposed framework, the target function is… read more here.
Keywords: regression problems; probabilistic partition; dimensional regression; partition unity ... See more keywords
Post-transfer learning statistical inference in high-dimensional regression
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DOI: 10.1007/s11222-025-10738-z
Abstract: Transfer learning (TL) for high-dimensional regression (HDR) is an important problem in machine learning, particularly when dealing with limited sample size in the target task. However, there currently lacks a method to quantify the statistical… read more here.
Keywords: transfer learning; inference; high dimensional; statistical inference ... See more keywords
Honest Confidence Sets for High-Dimensional Regression by Projection and Shrinkage*
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DOI: 10.1080/01621459.2021.1938581
Abstract: The issue of honesty in constructing confidence sets arises in nonparametric regression. While optimal rate in nonparametric estimation can be achieved and utilized to construct sharp confidence sets, severe degradation of confidence level often happens… read more here.
Keywords: high dimensional; confidence sets; confidence; dimensional regression ... See more keywords
The conditionality principle in high-dimensional regression
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DOI: 10.1093/biomet/asz015
Abstract: Consider a high-dimensional linear regression problem, where the number of covariates is larger than the number of observations and the interest is in estimating the conditional variance of the response variable given the covariates. A… read more here.
Keywords: regression; high dimensional; dimensional regression; marginal distribution ... See more keywords
Debiased high-dimensional regression calibration for errors-in-variables log-contrast models.
Sign Up to like & getrecommendations! Published in 2024 at "Biometrics"
DOI: 10.1093/biomtc/ujae153
Abstract: Motivated by the challenges in analyzing gut microbiome and metagenomic data, this work aims to tackle the issue of measurement errors in high-dimensional regression models that involve compositional covariates. This paper marks a pioneering effort… read more here.
Keywords: debiased high; high dimensional; log contrast; dimensional regression ... See more keywords