Jump detection in generalized error-in-variables regression with an application to Australian health tax policies

Yicheng Kang, Xiaodong Gong, Jiti Gao, Peihua Qiu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Without measurement errors in predictors, discontinuity of a nonparametric regression function at unknown locations could be estimated using a number of existing approaches. However, it becomes a challenging problem when the predictors contain measurement errors. In this paper, an error-invariables jump point estimator is suggested for a nonparametric generalized error-in-variables regression model. A major feature of our method is that it does not impose any parametric distribution on the measurement error. Its performance is evaluated by both numerical studies and theoretical justifications. The method is applied to studying the impact of Medicare Levy Surcharge on the private health insurance take-up rate in Australia.
Original languageEnglish
Pages (from-to)883 - 900
Number of pages18
JournalThe Annals of Applied Statistics
Volume9
Issue number2
DOIs
Publication statusPublished - 2015

Cite this

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abstract = "Without measurement errors in predictors, discontinuity of a nonparametric regression function at unknown locations could be estimated using a number of existing approaches. However, it becomes a challenging problem when the predictors contain measurement errors. In this paper, an error-invariables jump point estimator is suggested for a nonparametric generalized error-in-variables regression model. A major feature of our method is that it does not impose any parametric distribution on the measurement error. Its performance is evaluated by both numerical studies and theoretical justifications. The method is applied to studying the impact of Medicare Levy Surcharge on the private health insurance take-up rate in Australia.",
author = "Yicheng Kang and Xiaodong Gong and Jiti Gao and Peihua Qiu",
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journal = "The Annals of Applied Statistics",
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Jump detection in generalized error-in-variables regression with an application to Australian health tax policies. / Kang, Yicheng; Gong, Xiaodong; Gao, Jiti; Qiu, Peihua.

In: The Annals of Applied Statistics, Vol. 9, No. 2, 2015, p. 883 - 900.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Kang, Yicheng

AU - Gong, Xiaodong

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AU - Qiu, Peihua

PY - 2015

Y1 - 2015

N2 - Without measurement errors in predictors, discontinuity of a nonparametric regression function at unknown locations could be estimated using a number of existing approaches. However, it becomes a challenging problem when the predictors contain measurement errors. In this paper, an error-invariables jump point estimator is suggested for a nonparametric generalized error-in-variables regression model. A major feature of our method is that it does not impose any parametric distribution on the measurement error. Its performance is evaluated by both numerical studies and theoretical justifications. The method is applied to studying the impact of Medicare Levy Surcharge on the private health insurance take-up rate in Australia.

AB - Without measurement errors in predictors, discontinuity of a nonparametric regression function at unknown locations could be estimated using a number of existing approaches. However, it becomes a challenging problem when the predictors contain measurement errors. In this paper, an error-invariables jump point estimator is suggested for a nonparametric generalized error-in-variables regression model. A major feature of our method is that it does not impose any parametric distribution on the measurement error. Its performance is evaluated by both numerical studies and theoretical justifications. The method is applied to studying the impact of Medicare Levy Surcharge on the private health insurance take-up rate in Australia.

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DO - 10.1214/15-AOAS814

M3 - Article

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SP - 883

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JO - The Annals of Applied Statistics

JF - The Annals of Applied Statistics

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