One-step regularized estimator for high-dimensional regression models (Q6621326)

scientific article; zbMATH DE number 7928653

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English	One-step regularized estimator for high-dimensional regression models	scientific article; zbMATH DE number 7928653

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instance of

scholarly article

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title

One-step regularized estimator for high-dimensional regression models (English)

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18 October 2024

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zbMATH Keywords

confidence intervals

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high-dimension regression

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M-estimation

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one-step regularized estimators

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semiparametric model

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MaRDI profile type

Publication

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cites work

Penalized Composite Quasi-Likelihood for Ultrahigh Dimensional Variable Selection

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Statistics for high-dimensional data. Methods, theory and applications.

0 references

The Dantzig selector: statistical estimation when $p$ is much larger than $n$. (With discussions and rejoinder).

0 references

Asymptotic properties of the residual bootstrap for Lasso estimators

0 references

Bootstrapping Lasso Estimators

0 references

Sieve Extremum Estimates for Weakly Dependent Data

0 references

Double/debiased machine learning for treatment and structural parameters

0 references

High-dimensional simultaneous inference with the bootstrap

0 references

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

0 references

Nonconcave Penalized Likelihood With NP-Dimensionality

0 references

Drawing inferences for high‐dimensional linear models: A selection‐assisted partial regression and smoothing approach

0 references

Nonparametric maximum likelihood estimation by the method of sieves

0 references

Variable selection in nonparametric additive models

0 references

Exploration, normalization, and summaries of high density oligonucleotide array probe level data

0 references

Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory

0 references

Debiasing the Lasso: optimal sample size for Gaussian designs

0 references

Asymptotics for Lasso-type estimators.

0 references

Inference in Additively Separable Models With a High-Dimensional Set of Conditioning Variables

0 references

Exact post-selection inference, with application to the Lasso

0 references

A significance test for the lasso

0 references

Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model

0 references

High-dimensional graphs and variable selection with the Lasso

0 references

Instrumental Variable Estimation of Nonparametric Models

0 references

A general theory of hypothesis tests and confidence regions for sparse high dimensional models

0 references

Asymptotic normality and optimalities in estimation of large Gaussian graphical models

0 references

Estimating the dimension of a model

0 references

Convergence rate of sieve estimates

0 references

Q4864293

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On asymptotically optimal confidence regions and tests for high-dimensional models

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High-dimensional generalized linear models and the lasso

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

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Model Selection and Estimation in Regression with Grouped Variables

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Nearly unbiased variable selection under minimax concave penalty

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The sparsity and bias of the LASSO selection in high-dimensional linear regression

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Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models

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Q3174050

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published in

STATISTICA SINICA

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Identifiers

DOI

10.5705/ss.202022.0065

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Mathematics Subject Classification ID

62-XX

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zbMATH DE Number

7928653

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Sitelinks

Mathematics(1 entry)

mardi Publication:6621326