Estimation with Sequential Order Statistics from Exponential Distributions
By Erhard Cramer, Udo Kamps. 2001
85 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/384e24e8afe3b17b3ba5efbf98e0e65c373b0953
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In Statistics and Probability
- M. Maswadah
- Erhard Cramer
- George Iliopoulos
- Udo Kamps
- Narayanaswamy Balakrishnan
- Zeinhum F. Jaheen
- Umesh Singh
- Sanjay Kumar Singh
Citations in the corpus
- Relations for expectations of functions of generalized order statistics (2000, background): “(vi) Since progressive type II censored order statistics can be seen as generalized order statistics (cf. Kamps 1995a, Cramer and Kamps 2000), the relations (2.5) and (2.6), respectively, are valid for this censoring scheme as well.”
- On Bayesian predictive distributions of generalized order statistics (2003, unknown): “Cramer and Kamps (2001) proposed the use of sequential order statistics to model a change of the residual liftime distribution after the breakdown of some component in a k-out-of-n system based on a one – and two-parameter exponential distributions.”
- Adaptive progressive Type-II censoring (2010, methodology): “So, independently of the adaptive progressive censoring scheme, everything works exactly as in the deterministic model (cf. Balakrishnan and Aggarwala 2000 and Cramer and Kamps 2001a).”
- Conditional confidence interval estimation for the inverse weibull distribution based on censored generalized order statistics (2003, background): “3) from which the conditional pdf of Z1 and Z2 given A 1⁄4 (a1, a2, . . . , ar 2) can be obtained as in (2.3). j The details of the proof are similar to that for finding the conditional pdf of Z1 and Z2 given A 1⁄4 (a1, a2, . . . , ar 2) based on the ordinary censored sample given by Lawless (1982),”
- Marginal distributions of sequential and generalized order statistics (2003, background): “Cramer and Kamps, 2001a ), where Z ð1Þ ; ... ; Z ðrÞ are independent and Z ðjÞ has an exponential distribution with parameter cj ,1 � j � r. Hence, generalized order statistics from exponential distributions are sums of independent random variables with possibly nonidentical exponential distribution”