Results 21 to 30 of about 22,216,553 (297)
Assessment of non-linearity in calorie–income relationship in Pakistan
This article considers the issue of assessing non-linearity in the relationship between calorie consumption and income using non-parametric and semi-parametric approaches.
Nadia Shabnam
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Semiparametric Integrated and Additive Spatio-Temporal Single-Index Models
In this paper, we introduce two semiparametric single-index models for spatially and temporally correlated data. Our first model has spatially and temporally correlated random effects that are additive to the nonparametric function, which we refer to as ...
Hamdy F. F. Mahmoud, Inyoung Kim
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Analysis of Double Single Index Models [PDF]
Abstract Motivated from problems in canonical correlation analysis, reduced rank regression and sufficient dimension reduction, we introduce a double dimension reduction model where a single index of the multivariate response is linked to the multivariate covariate through a single index of these covariates, hence the name double ...
Chen, Kun, Ma, Yanyuan
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A short note on fitting a single-index model with massive data
This paper studies the inference problem of index coefficient in single-index models under massive dataset. Analysis of massive dataset is challenging owing to formidable computational costs or memory requirements.
Rong Jiang, Yexun Peng
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Estimation in monotone single‐index models [PDF]
Single‐index models are popular regression models that are more flexible than linear models and still maintain more structure than purely nonparametric models. We consider the problem of estimating the regression parameters under a monotonicity constraint on the unknown link function.
Piet Groeneboom, Kim Hendrickx
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The Single Index Market Model in Agriculture [PDF]
This study illustrates the differences in empirical results due to data measurements and estimating procedures when applying the single index market model in agriculture. Gross and net return betas along with systematic and unsystematic risk proportions are estimated and found to be different.
Gempesaw, Conrado M., II +3 more
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Let $(\bX, Y)$ be a random pair taking values in $\mathbb R^p \times \mathbb R$. In the so-called single-index model, one has $Y=f^{\star}(θ^{\star T}\bX)+\bW$, where $f^{\star}$ is an unknown univariate measurable function, $θ^{\star}$ is an unknown vector in $\mathbb R^d$, and $W$ denotes a random noise satisfying $\mathbb E[\bW|\bX]=0$.
Alquier, Pierre, Biau, Gérard
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A single-index quantile regression model and its estimation [PDF]
Models with single-index structures are among the many existing popular semiparametric approaches for either the conditional mean or the conditional variance. This paper focuses on a single-index model for the conditional quantile. We propose an adaptive
Xia, Y. +3 more
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On Single-Index Models beyond Gaussian Data
Sparse high-dimensional functions have arisen as a rich framework to study the behavior of gradient-descent methods using shallow neural networks, showcasing their ability to perform feature learning beyond linear models. Amongst those functions, the simplest are single-index models $f(x) = ϕ( x \cdot θ^*)$, where the labels are generated by an ...
Aaron Zweig +2 more
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Score Tests for the Single Index Model [PDF]
The single index model is a generalization of the linear regression model with E(y|x) = g(x′β), where g is an unknown function. The model provides a flexible alternative to the linear regression model while providing more structure than a fully nonparametric approach.
Jeffrey S. Simonoff, Chih-Ling Tsai
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