High dimensional single index models

Web1 de jan. de 2024 · Abstract. We consider a flexible semiparametric single-index quantile regression model where the number of covariates may be ultra-high dimensional, and the number of the relevant covariates is potentially diverging. The approach is particularly appealing to uncover the complex heterogeneity in high-dimensional data, incorporate … Web17 de mai. de 2024 · We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link function is unknown, but constrained with monotone and non-decreasing shape. We develop a scalable projection-based iterative approach, the …

Tests for high-dimensional single-index models

WebNon-Gaussian Single Index Models via Thresholded Score Function Estimation 1.1. Challenges of the Single Index Models There are significant challenges that appear when we are dealing with estimators for SIMs. They can be summa-rized as assumptions on either the link function or the data distribution (for example, non-Gaussian assumption). 1. Web11 de abr. de 2024 · Model checking methods based on non-parametric estimation are widely used because of their tractable limiting null distributions and being sensitive to high-frequency oscillation alternative models. However, this kind of test suffers from the curse of dimensionality, resulting in slow convergence, especially for functional data with infinite … iqac report format https://jamconsultpro.com

(PDF) Tests for high-dimensional single-index models

Web1 de dez. de 2016 · To treat higher dimensional predictors, the estimation procedure must be accompanied by a variable selection step. Recently, several approaches have been … Web13 de mar. de 2016 · Single Index Models (SIMs) are simple yet flexible semi- parametric models for machine learning, where the response variable is modeled as a monotonic function of a linear combination of features. Estimation in this context requires learning both the feature weights and the nonlinear function that relates features to observations. … Webinvolves only high-dimensional parameters. The strategy for the high-dimensional single-index model does not work for the model (1.1), which has multiple index-es and specific structure. In the paper, we provide a semiparametrically efficient and computationally convenient estimator for all of parameters and functions in high-dimensional SMIM. iqa world cup

High dimensional single index models - ScienceDirect

Category:Robust inference for high‐dimensional single index models

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High dimensional single index models

Impedance spectroscopy : theory, experiment, and applications

Web1 de mai. de 2024 · In this article, we study the estimation of high‐dimensional single index models when the response variable is censored. We hybrid the estimation methods for high‐dimensional single‐index ... Web1 de jul. de 2015 · 2024. TLDR. This work considers estimating the parametric component of single index models in high dimensions using Stein's Lemma to propose estimators …

High dimensional single index models

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WebThe problem of statistical inference for regression coefficients in a high-dimensional single-index model is considered. Under elliptical symmetry, the single index model can be reformulated as a proxy linear model whose regression parameter is identifiable. We construct estimates of the regression coefficients of interest that are similar to ... WebWe propose a robust inference method for high‐dimensional single index models with an unknown link function and elliptically symmetrically distributed covariates, focusing on signal recovery and inference. The proposed method is built on the Huber loss and the estimation of the unknown link function is avoided. The ℓ1$$ {\\ell}_1 $$ and ℓ2$$ {\\ell}_2 $$ …

Web27 de mar. de 2024 · Abstract. In this article, we leverage over-parameterization to design regularization-free algorithms for the high-dimensional single index model and provide theoretical guarantees for the induced implicit regularization phenomenon. Web30 de jun. de 2015 · Single Index Models (SIMs) are simple yet flexible semi-parametric models for classification and regression.Response variables are modeled as a …

Web11 de abr. de 2024 · The ICESat-2 mission The retrieval of high resolution ground profiles is of great importance for the analysis of geomorphological processes such as flow processes (Mueting, Bookhagen, and Strecker, 2024) and serves as the basis for research on river flow gradient analysis (Scherer et al., 2024) or aboveground biomass estimation (Atmani, … WebSingle-index models generalize linear regression. They have applications to a variety of fields, such as discrete choice analysis in econometrics and dose response models in biometrics, where high-dimensional regression models are often employed. Single-index models are similar to the first step of projection pursuit regression, a dimension …

WebAbstract. In this article, we consider the problem of hypothesis testing in high-dimensional single-index models. First, we study the feasibility of applying the classical F-test to a …

Web2 de fev. de 2024 · PDF On Feb 2, 2024, Leheng Cai and others published Tests for high-dimensional single-index models * Find, read and cite all the research you need on ResearchGate iqai share chathttp://proceedings.mlr.press/v70/yang17a/yang17a.pdf orchid gallery pittsboroWeb27 de mar. de 2024 · Abstract. In this article, we leverage over-parameterization to design regularization-free algorithms for the high-dimensional single index model and … iqa training recommendations memo sampleWeb20 de jun. de 2024 · Abstract. Single-index models are potentially important tools for multivariate nonparametric regression analysis. They generalize linear regression models by replacing the linear combination \alpha^T_0 with a nonparametric component \eta_0 ( {\alpha^T_0})X, where \eta_0 (\cdot) is an unknown univariate link function. iqa world cup 2023Web8 de set. de 2024 · Inference In General Single-Index Models Under High-dimensional Symmetric Designs. We consider the problem of statistical inference for a finite number of covariates in a generalized single-index model with p > n covariates and unknown (potentially random) link function under an elliptically symmetric design. Under elliptical … iqac scholarshipWeb3 de fev. de 2024 · Abstract We study the effects of high-dimensional covariates in the single-index quantile regression model. An improved version of an estimation algorithm is proposed with variable selection. Finite sample performance is studied through an extensive simulation study which highlights the performance of the new procedure. A data analysis … iqa valid authenticWebmodel via SGD with non-stationary, high-dimensional streaming data. Shi et al. (2024) in-troduced a valid inference method for single or low-dimensional regression coefficients … iqac type ii