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Varying-coefficient single-index model
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Heung Wong, Wai-Cheung Ip, Riquan Zhang
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Single-index relative error regression models
Communications in Statistics - Simulation and Computation, 2021We consider the estimation and hypothesis test for single-index model by proposing a profile mean squares relative error estimation method, coupling with a leave-one-component-out method.
Yujie Gai, Jun Zhang 0027
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SIMEX estimation for single-index model with covariate measurement error
AStA Advances in Statistical Analysis, 2016In this paper, we consider the single-index measurement error model with mismeasured covariates in the nonparametric part. To solve the problem, we develop a simulation-extrapolation (SIMEX) algorithm based on the local linear smoother and the estimating
Yi-Ping Yang, Tiejun Tong, Gaorong Li
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Computational-Statistical Gaps in Gaussian Single-Index Models
Annual Conference Computational Learning TheorySingle-Index Models are high-dimensional regression problems with planted structure, whereby labels depend on an unknown one-dimensional projection of the input via a generic, non-linear, and potentially non-deterministic transformation.
Alex Damian +3 more
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Estimation of a Functional Single Index Model
2011Single index models have been mostly studied as an alternative dimension reduction technique for nonparametric regression with multivariate covariates. The index parameter appearing in the model summarizes the effect of the covariates in a finite dimensional vector.
Ferraty, Frédéric +2 more
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On bootstrap consistency of MAVE for single index models
Computational Statistics & Data Analysis, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hong-Fan Zhang +2 more
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Least squares estimation in the monotone single index model
Bernoulli, 2016We study the monotone single index model where a real response variable $Y $ is linked to a $d$-dimensional covariate $X$ through the relationship $E[Y | X] = \Psi_0(\alpha^T_0 X)$ almost surely. Both the ridge function, $\Psi_0$, and the index parameter,
Fadoua Balabdaoui +2 more
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Biometrika, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Naik, Prasad A., Tsai, Chih-Ling
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Naik, Prasad A., Tsai, Chih-Ling
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Functional single-index quantile regression models
Statistics and Computing, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peijun Sang, Jiguo Cao
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1998
One of the most important tasks of applied econometrics and statistics is estimating a conditional mean function. For example, one may want to estimate the mean annual earnings of workers in a certain population as a function of observable characteristics such as level of education and experience in the workforce.
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One of the most important tasks of applied econometrics and statistics is estimating a conditional mean function. For example, one may want to estimate the mean annual earnings of workers in a certain population as a function of observable characteristics such as level of education and experience in the workforce.
openaire +1 more source