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Single-index model selections

Biometrika, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Naik, Prasad A., Tsai, Chih-Ling
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On bootstrap consistency of MAVE for single index models

Computational Statistics & Data Analysis, 2020
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Hong-Fan Zhang   +2 more
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Single-Index Model Tree

IEEE Transactions on Knowledge and Data Engineering, 2021
Agus Sudjianto   +2 more
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Single-Index Models

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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Nonlinear regression models with single‐index heteroscedasticity

Statistica Neerlandica, 2019
We consider nonlinear heteroscedastic single‐index models where the mean function is a parametric nonlinear model and the variance function depends on a single‐index structure. We develop an efficient estimation method for the parameters in the mean function by using the weighted least squares estimation, and we propose a “delete‐one‐component ...
Jun Zhang   +3 more
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Estimation for the single-index models with random effects

Computational Statistics & Data Analysis, 2012
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Pang, Zhen., Xue, Liugen.
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Latent single-index models for ordinal data

Statistics and Computing, 2017
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Zhiyong Chen, Hai-Bin Wang
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ERROR VARIANCE ESTIMATION FOR THE SINGLE‐INDEX MODEL

Australian & New Zealand Journal of Statistics, 2010
SummarySingle‐index models provide one way of reducing the dimension in regression analysis. The statistical literature has focused mainly on estimating the index coefficients, the mean function, and their asymptotic properties. For accurate statistical inference it is equally important to estimate the error variance of these models.
Kulasekera, K. B., Lin, Wei
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The single-index hazards model

2010
We first propose the single-index hazards model for right censored survival data. As an extension of the Cox model, this model allows nonparametric modeling of covariate effects in a parsimonious way via a single-index. In addition, the relative importance of covariates can be assessed via this model.
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