Journal ArticleDOI
A nonparametric test for covariate-adjusted models
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TLDR
In this article, a nonparametric test for covariate-adjusted models is proposed, obtained by using the adjusted response and predictors, and the proposed test statistic has the same limit distribution as when the response and predictor are observed directly.About:
This article is published in Statistics & Probability Letters.The article was published on 2018-02-01. It has received 33 citations till now. The article focuses on the topics: Goldfeld–Quandt test & Test statistic.read more
Citations
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Nonlinear regression models with general distortion measurement errors
TL;DR: The authors consider nonlinear regression models when neither the response variable nor the covariates can be directly observed, but are measured with both multiplicative and additive distortion, and show that both additive distortion and multiplicative distortion can be used.
Journal ArticleDOI
A goodness-of-fit test for variable-adjusted models
TL;DR: This research provides a projection-based test to check parametric single-index regression structure in variable-adjusted models and an adaptive-to-model strategy is employed, which makes the proposed test work better on the significance level maintenance and more powerful than existing tests.
Journal ArticleDOI
Multiplicative regression models with distortion measurement errors
TL;DR: In this paper, the authors considered the problem of variable selection for multiplicative linear regression models when neither the response variable nor the covariates can be directly observed, but are distorted by unknown functions of a commonly observable confounding variable.
Journal ArticleDOI
Logarithmic calibration for multiplicative distortion measurement errors regression models
Jun Zhang,Yiping Yang,Gaorong Li +2 more
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Estimation and variable selection for partial linear single-index distortion measurement errors models
TL;DR: In this paper, the conditional absolute mean calibration (COMC) method is proposed to eliminate the effect caused by the distortion, which avoids to use the nonzero expectation conditions imposed on the variables in the literature.
References
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Journal ArticleDOI
A consistent test of functional form via nonparametric estimation techniques
TL;DR: In this paper, the conditional moment test is combined with nonparametric estimation techniques and the test statistic is shown to be asymptotically distributed standard normal under the null hypothesis that the parametric model is correct, while diverging to infinity at a rate arbitrarily close to n.
Journal ArticleDOI
Asymptotics for kernel estimate of sliced inverse regression
Lixing Zhu,Kai-Tai Fang +1 more
TL;DR: In this article, the asymptotic properties of the kernel estimate of sliced inverse regression are investigated, and it turns out that regardless of kernel function, the distribution remains the same for a wide range of smoothing parameters.
Journal ArticleDOI
Inference for covariate adjusted regression via varying coefficient models
Damla Şentürk,Hans-Georg Müller +1 more
TL;DR: In this article, the covariate adjusted regression (CAR) method is used to estimate the asymptotic normality of the estimates by establishing a connection to varying coefficient models.
Journal ArticleDOI
Covariate-adjusted nonlinear regression
TL;DR: In this paper, a covariate-adjusted nonlinear regression model is proposed to estimate the distorting functions by nonparametrically regressing the predictors and response on a distorting covariate; then, nonlinear least squares estimators for the parameters are obtained using the estimated response and predictors.
Journal ArticleDOI
Minimum distance regression model checking
Hira L. Koul,Pingping Ni +1 more
TL;DR: The paper establishes the asymptotic normality of the proposed test statistics and that of the corresponding minimum distance estimators under the fitted model as n1/2-consistent.
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