Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Multi-Stage Interval Estimations of the Largest Mean of k Normal Populations

Yung Liang Tong
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 32, No. 2 (1970), pp. 272-277
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2984533
Page Count: 6
  • Read Online (Free)
  • Download ($29.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Multi-Stage Interval Estimations of the Largest Mean of k Normal Populations
Preview not available

Abstract

We have k normal populations (k ⩾ 1) with means θ12,...,θk and a common unknown variance σ2. A fixed-width confidence interval for θ* = max1 ⩽ i ⩽ k θi is desired so that the coverage probability is at least γ (preassigned) for every θ = (θ12,⋯,θk) and $\sigma^2 > 0$. A class of multistage procedures is considered for the solution of this problem. It is shown that at least for k ⩽ 2, the efficiencies of those procedures are always less than one.

Page Thumbnails

  • Thumbnail: Page 
272
    272
  • Thumbnail: Page 
273
    273
  • Thumbnail: Page 
274
    274
  • Thumbnail: Page 
275
    275
  • Thumbnail: Page 
276
    276
  • Thumbnail: Page 
277
    277