A modified Liu-type estimator with an intercept term under mixture experiments

Ai Chun Chen, Takeshi Emura*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

2 Scopus citations


We consider ridge regression with an intercept term under mixture experiments. We propose a new estimator which is shown to be a modified version of the Liu-type estimator. The so-called compound covariate estimator is applied to modify the Liu-type estimator. We then derive a formula of the total mean squared error (TMSE) of the proposed estimator. It is shown that the new estimator improves upon existing estimators in terms of the TMSE, and the performance of the new estimator is invariant under the change of the intercept term. We demonstrate the new estimator using a real dataset on mixture experiments.

Original languageEnglish
Pages (from-to)6645-6667
Number of pages23
JournalCommunications in Statistics - Theory and Methods
Issue number13
StatePublished - 03 07 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Taylor & Francis Group, LLC.


  • Compound covariate estimator
  • least squares estimator
  • linear regression
  • ridge regression
  • shrinkage estimator


Dive into the research topics of 'A modified Liu-type estimator with an intercept term under mixture experiments'. Together they form a unique fingerprint.

Cite this