Name
Abstract | ||
|---|---|---|
Maximum likelihood estimates may not exist for some distributions. One way to deal with this problem is to derive the so-called embedded distributions. In computer programming, it is important to know whether or not the maximum likelihood estimates for the original distribution exists, that is, whether or not an embedded distribution occurs. This paper provides a criterion for this purpose. The criterion, which we term the “Δ-discriminant”, is derived by evaluating the difference of the log-likelihood functions between the original distribution and the corresponding embedded distribution around the point of the maximum likelihood estimates for the embedded distribution. As applications, we provide the Δ-discriminants for some commonly used distributions in the presence of both left-censored and right-censored observations. Some published data sets are used to illustrate our results. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/S0167-9473(03)00171-3 | Computational Statistics & Data Analysis |
Keywords | DocType | Volume |
Burr type III distribution,Burr type XII distribution,Δ-discriminant,Embedded model problem,Gamma distribution,Inverse Gaussian distribution,Left-censored observations,Lognormal distribution,Pareto distribution,Right-censored observations,Weibull distribution | Journal | 46 |
Issue | ISSN | Citations |
2 | 0167-9473 | 1 |
PageRank | References | Authors |
0.73 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Quanxi Shao | 1 | 25 | 8.69 |
| Wai-Cheung Ip | 2 | 27 | 11.72 |
| Heung Wong | 3 | 80 | 22.74 |