Estimation of total time on test transforms for stationary observations
By proving Chibisov-O'Reilly-type theorems for uniform empirical and quantile processes based on stationary observations, we establish a nonparametric large sample estimation theory for total time on test transforms. In particular, we obtain weak approximations for total time on test transforms also under the assumption of positively associated dependence, a kind of dependence that is encountered in many practical life testing situations. We derive similar asymptotic results for mixing sequences as well, another and often used structure of dependence for sequences.
Year of publication: |
1997
|
---|---|
Authors: | Csörgo, Miklós ; Yu, Hao |
Published in: |
Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 68.1997, 2, p. 229-253
|
Publisher: |
Elsevier |
Keywords: | Total time on test Life testing Empirical processes Quantile processes Weighted metrics Stationarity Positive Association Mixing |
Saved in:
Saved in favorites
Similar items by person
-
Uncertainty and risk analysis of the Langrun Chinese GDP Forecast : fan charts revisited
Yu, Hao, (2011)
-
China's medical savings accounts : an analysis of the price elasticity of demand for health care
Yu, Hao, (2017)
-
Global Strassen-type theorems for iterated Brownian motions
Csáki, Endre, (1995)
- More ...