A correction note on "semiparametric transformation models and the missing information principle"

Sundarraman Subramanian

doi:10.1016/j.jspi.2003.07.006

A correction note on "semiparametric transformation models and the missing information principle"

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

Abstract

This note provides a corrected estimating function for the regression parameter in the linear transformation model with censored data, analyzed by Subramanian (J. Statist. Plann. Inference 115 (2003) 327).

Original language	English (US)
Pages (from-to)	397-399
Number of pages	3
Journal	Journal of Statistical Planning and Inference
Volume	126
Issue number	1
DOIs	https://doi.org/10.1016/j.jspi.2003.07.006
State	Published - Nov 1 2004
Externally published	Yes

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

Keywords

Estimating function
Least squares
Linear transformation model

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10.1016/j.jspi.2003.07.006

Cite this

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abstract = "This note provides a corrected estimating function for the regression parameter in the linear transformation model with censored data, analyzed by Subramanian (J. Statist. Plann. Inference 115 (2003) 327).",

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N2 - This note provides a corrected estimating function for the regression parameter in the linear transformation model with censored data, analyzed by Subramanian (J. Statist. Plann. Inference 115 (2003) 327).

AB - This note provides a corrected estimating function for the regression parameter in the linear transformation model with censored data, analyzed by Subramanian (J. Statist. Plann. Inference 115 (2003) 327).

KW - Estimating function

KW - Least squares

KW - Linear transformation model

UR - https://www.scopus.com/pages/publications/4444234558

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JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

IS - 1

ER -

A correction note on "semiparametric transformation models and the missing information principle"

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

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