Influence diagnostics in the tobit censored response model

Michelli Barros; Manuel Galea; Manuel González; Víctor Leiva

doi:10.1007/s10260-010-0135-y

Influence diagnostics in the tobit censored response model

Michelli Barros, Manuel Galea, Manuel González, Víctor Leiva

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.

Original language	English
Pages (from-to)	379-397
Number of pages	19
Journal	Statistical Methods and Applications
Volume	19
Issue number	3
DOIs	https://doi.org/10.1007/s10260-010-0135-y
State	Published - 2010
Externally published	Yes

Keywords

Cook distance
Likelihood methods
Local influence
Residual analysis

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10.1007/s10260-010-0135-y

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title = "Influence diagnostics in the tobit censored response model",

abstract = "In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.",

keywords = "Cook distance, Likelihood methods, Local influence, Residual analysis",

author = "Michelli Barros and Manuel Galea and Manuel Gonz{\'a}lez and V{\'i}ctor Leiva",

note = "Funding Information: Acknowledgments The authors wish to thank the editors and referees for their helpful comments that aided in improving this article. This study was partially supported by CNPq (Casadinho 620150/2008-4, Universal-477747/2008-6, PROSUL-490429/2008-4 and INCTMat-57.33523/2008-8), Brazil, and FOND-ECYT (1070919 and 1080326) and DIPUV 29-2006 grants, Chile.",

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doi = "10.1007/s10260-010-0135-y",

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T1 - Influence diagnostics in the tobit censored response model

AU - Barros, Michelli

AU - Galea, Manuel

AU - González, Manuel

AU - Leiva, Víctor

N1 - Funding Information: Acknowledgments The authors wish to thank the editors and referees for their helpful comments that aided in improving this article. This study was partially supported by CNPq (Casadinho 620150/2008-4, Universal-477747/2008-6, PROSUL-490429/2008-4 and INCTMat-57.33523/2008-8), Brazil, and FOND-ECYT (1070919 and 1080326) and DIPUV 29-2006 grants, Chile.

PY - 2010

Y1 - 2010

N2 - In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.

AB - In this article, we develop influence diagnostic tools for the tobit model. Specifically, we discuss global influence methods based on the Cook distance and residuals with envelopes, and total and conformal local influence techniques. In order to analyze the sensitivity of the maximum likelihood estimators of the parameters of the model to small perturbations on the assumptions of the model and/or data, we consider several perturbation schemes, such as case-weight and response perturbations. Finally, we illustrate the developed methodology by means of a real data set.

KW - Cook distance

KW - Likelihood methods

KW - Local influence

KW - Residual analysis

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SN - 1618-2510

VL - 19

SP - 379

EP - 397

JO - Statistical Methods and Applications

JF - Statistical Methods and Applications

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ER -

Influence diagnostics in the tobit censored response model

Abstract

Keywords

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