Start Submission Become a Reviewer

Reading: Multiple Crossing Sequential Fixed-Size Confidence Regions for Regression Parameters Under N...

Download

A- A+
dyslexia friendly

Articles

Multiple Crossing Sequential Fixed-Size Confidence Regions for Regression Parameters Under Normality

Authors:

Sankha Muthu Poruthotage,

Plymouth Rock Assurance Company, Boston, Department of Statistics, University of Connecticut,, US
X close

Nitis Mukhopadhyay

Department of Statistics, University of Connecticut,, US
X close

Abstract

The purely sequential sampling procedure proposed by Mukhopadhyay and Abid (1986) is customarily used to construct a fixed-size confidence region for regression parameters. This methodology has asymptotic efficiency and asymptotic consistency properties, but it does not have the exact consistency property. We propose that sequential sampling be continued allowing the sample size to cross a corresponding boundary multiple times. The asymptotic efficiency and asymptotic consistency properties are ascertained for multiple crossing stopping rules (Theorem 2.1). A truncation technique as well as a fine-tuning adjustment are developed. The simulated data are generated by realistic models arising from a study that investigates the association between prostate-specific antigen (PSA) and a number of appropriate prognostic clinical covariates. We highlight via large-scale simulations the remarkable gain in nearly achieving the target coverage without significant over-sampling.

DOI: http://dx.doi.org/10.4038/sljastats.v5i4.7789

How to Cite: Poruthotage, S.M. & Mukhopadhyay, N., (2014). Multiple Crossing Sequential Fixed-Size Confidence Regions for Regression Parameters Under Normality. Sri Lankan Journal of Applied Statistics. 5(4), pp.147–182. DOI: http://doi.org/10.4038/sljastats.v5i4.7789
Published on 15 Dec 2014.
Peer Reviewed

Downloads

  • PDF (EN)

    comments powered by Disqus