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פותח על ידי קלירמאש פתרונות בע"מ -
Three stage elimination type procedures for selecting the best normal population when variances are unknown
Year:
1981
Authors :
מרכוס, רות
;
.
Volume :
10
Co-Authors:
Hochberg, Y., University of Tel Aviv, Ramat-Aviv, Israel
Marcus, R., University of Tel Aviv, Ramat-Aviv, Israel
Facilitators :
From page:
597
To page:
612
(
Total pages:
16
)
Abstract:
The problem of selecting the normal population with largest mean when variances are unknown, is considered. A three stage procedure is proposed. Based on pilot samples of size n from (2 > (> ° each population the total sizes N. > N., f>n) of the two following stages are determined. In the second stage one takes N-n additional observations from the ith population and i o, eliminates a random subset of “bad11 populations. If only one population remains after the second stage we make our final selection at that point; if more than one pppulation remains, we proceed to the third stage. In that case additional -N (1) (2) N. observations are drawn from the ith non-eliminated population and a final selection is then made. A simple conservative procedure is derived and compared with corresponding non-elimination procedures on a restricted set of simulated data. The numerical data show that phe new procedure will be very economical in many realistic applications. Another procedure which is shown to be exact over a “slippage zone” is discussed in an Appendix. © 1981, Taylor & Francis Group, LLC. All rights reserved.
Note:
Related Files :
indifference zone
selection of a best normal population
unknown variances elimination procedures
עוד תגיות
תוכן קשור
More details
DOI :
10.1080/03610928108828060
Article number:
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
26225
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:21
Scientific Publication
Three stage elimination type procedures for selecting the best normal population when variances are unknown
10
Hochberg, Y., University of Tel Aviv, Ramat-Aviv, Israel
Marcus, R., University of Tel Aviv, Ramat-Aviv, Israel
Three stage elimination type procedures for selecting the best normal population when variances are unknown
The problem of selecting the normal population with largest mean when variances are unknown, is considered. A three stage procedure is proposed. Based on pilot samples of size n from (2 > (> ° each population the total sizes N. > N., f>n) of the two following stages are determined. In the second stage one takes N-n additional observations from the ith population and i o, eliminates a random subset of “bad11 populations. If only one population remains after the second stage we make our final selection at that point; if more than one pppulation remains, we proceed to the third stage. In that case additional -N (1) (2) N. observations are drawn from the ith non-eliminated population and a final selection is then made. A simple conservative procedure is derived and compared with corresponding non-elimination procedures on a restricted set of simulated data. The numerical data show that phe new procedure will be very economical in many realistic applications. Another procedure which is shown to be exact over a “slippage zone” is discussed in an Appendix. © 1981, Taylor & Francis Group, LLC. All rights reserved.
Scientific Publication
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