A New Method for Estimating Inverse Data from Destructive Regular Storage Life Test

DOI

10.2991/cisia-15.2015.189How to use a DOI?

Keywords

inverse data; isotonic regression; minimum chi-square estimation; coefficient of variation

Abstract

In the destructive regular storage life test of products, there is "inverse" data sometimes, resulting in inaccurate estimates of its reliability index. Based on the theory of isotonic regression and minimum chi-square estimation, we proposed a new method for processing "inverse" data. First, alter the possible “inverse” of original frequency into the frequency meeting sequence constraint by using PAVA algorithm. Then, estimate reliability parameters by means of minimum chi-square estimation. Comparing with traditional methods, we increased the distribution-test of overall failure probability function, the point estimates and confidence intervals of reliability parameters during storage period of products. Finally, example shows that the coefficient of variation obtained by this method are smaller than MLE and the coefficient of variation changes little when sample size changes, reflecting its superiority for estimating small sample data.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - H. Wang
AU  - X.B Ma
PY  - 2015/06
DA  - 2015/06
TI  - A New Method for Estimating Inverse Data from Destructive Regular Storage Life Test
BT  - Proceedings of the International Conference on Computer Information Systems and Industrial Applications
PB  - Atlantis Press
SP  - 693
EP  - 696
SN  - 2352-538X
UR  - https://doi.org/10.2991/cisia-15.2015.189
DO  - 10.2991/cisia-15.2015.189
ID  - Wang2015/06
ER  -