Name
Abstract | ||
|---|---|---|
Based on the k-record values, inference is considered for the parameters of the Kumaraswamy distribution. The maximum likelihood estimates and alternative point estimates based on proposed pivotal quantities are provided for the unknown model parameters, and series of exact confidence intervals and exact confidence regions are constructed as well. For the confidence intervals and regions, the corresponding smallest-size confidence sets and their optimization procedures are presented based on minimizing the Lagrangian functions under given significance level. Two illustrative examples based on real and simulated data are provided to assess the performance of the proposed results. Maximum likelihood and pivotal based point estimates were proposed for Kumaraswamy model.Exact confidence intervals and regions are constructed for Kumaraswamy parameter.Pivotal based estimation methods can be extend to other model and failure samples cases.The smallest-sets are provided through constrained optimization problems.Monthly water capacity and simulated data examples are investigated. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.cam.2017.02.037 | J. Computational Applied Mathematics |
Keywords | Field | DocType |
Kumaraswamy distribution,k-records,Pivotal quantities,Maximum likelihood estimation,Optimal confidence sets,Nonlinear programming | Point estimation,Confidence distribution,Mathematical optimization,Kumaraswamy distribution,Inference,Nonlinear programming,Maximum likelihood,Confidence interval,Mathematics,Constrained optimization | Journal |
Volume | Issue | ISSN |
321 | C | 0377-0427 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liang Wang | 1 | 1567 | 158.46 |