Distribution-free prediction intervals for order statistics based on record coverage
Year
: 2011
Abstract: In this paper, based on the largest and smallest observations at the times when a new record
of either kind (upper or lower) occurs, we discuss the prediction of future order statistics.
The proposed prediction intervals are distribution-free in that the corresponding coverage
probabilities are known exactly without any assumption about the parent distribution
other than that it being continuous. An exact expression for the prediction coefficient
of these intervals is derived. Similarly, prediction intervals for future records based on
observed order statistics are also obtained. Finally, two real-life data, one involving the
average July temperatures in Neurenburg, Switzerland, and the other involving the amount
of annual rainfall at the Los Angeles Civic Center, are used to illustrate the procedures
developed here.
of either kind (upper or lower) occurs, we discuss the prediction of future order statistics.
The proposed prediction intervals are distribution-free in that the corresponding coverage
probabilities are known exactly without any assumption about the parent distribution
other than that it being continuous. An exact expression for the prediction coefficient
of these intervals is derived. Similarly, prediction intervals for future records based on
observed order statistics are also obtained. Finally, two real-life data, one involving the
average July temperatures in Neurenburg, Switzerland, and the other involving the amount
of annual rainfall at the Los Angeles Civic Center, are used to illustrate the procedures
developed here.
Keyword(s): Coverage probability
Current records
Prediction intervals
Record coverage
Order statistics
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Distribution-free prediction intervals for order statistics based on record coverage
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| contributor author | جعفر احمدی | en |
| contributor author | N. Balakrishnan | en |
| contributor author | Jafar Ahmadi | fa |
| date accessioned | 2020-06-06T14:33:32Z | |
| date available | 2020-06-06T14:33:32Z | |
| date issued | 2011 | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3401813 | |
| description abstract | In this paper, based on the largest and smallest observations at the times when a new record of either kind (upper or lower) occurs, we discuss the prediction of future order statistics. The proposed prediction intervals are distribution-free in that the corresponding coverage probabilities are known exactly without any assumption about the parent distribution other than that it being continuous. An exact expression for the prediction coefficient of these intervals is derived. Similarly, prediction intervals for future records based on observed order statistics are also obtained. Finally, two real-life data, one involving the average July temperatures in Neurenburg, Switzerland, and the other involving the amount of annual rainfall at the Los Angeles Civic Center, are used to illustrate the procedures developed here. | en |
| language | English | |
| title | Distribution-free prediction intervals for order statistics based on record coverage | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | Coverage probability Current records Prediction intervals Record coverage Order statistics | en |
| journal title | Journal of the Korean Statistical Society | fa |
| pages | 181-192 | |
| journal volume | 40 | |
| journal issue | 2 | |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1018968.html | |
| identifier articleid | 1018968 |