Likelihood inference under the general response transformation model with heteroscedastic errors

Chih-Rung Chen*, Lih Chung Wang

*Corresponding author for this work

Research output: Contribution to journalReview article

Abstract

In this paper, we propose the likelihood inference under the general response transformation model with heteroscedastic errors when the range of the response transformation is possibly different from the whole real line. Three commonly used families of response transformations are reviewed to illustrate the importance and applicability of the proposed model.

Original languageEnglish
Pages (from-to)261-273
Number of pages13
JournalTaiwanese Journal of Mathematics
Volume7
Issue number2
DOIs
StatePublished - 1 Jan 2003

Keywords

  • Folded power transformation
  • Heteroscedasticity
  • Likelihood inference
  • Modulus power transformation
  • Power transformation
  • Response transformation

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