Statistical analysis of extreme values
Statistical analysis of extreme values
Comparison of time series using subsampling
Computational Statistics & Data Analysis
Risk assessment for highway projects using jackknife technique
Expert Systems with Applications: An International Journal
| Hi-index | 0.03 |
For a sequence of independent, identically distributed random variables any limiting point process for the time normalized exceedances of high levels is a Poisson process. However, for stationary dependent sequences, under general local and asymptotic dependence restrictions, any limiting point process for the time normalized exceedances of high levels is a compound Poisson process, i.e., there is a clustering of high exceedances, where the underlying Poisson points represent cluster positions, and the multiplicities correspond to the cluster sizes. For such classes of stationary sequences there exists the extremal index@q, 0=0 for ''almost all'' cases of interest. The estimation of the extremal index through the use of the Generalized Jackknife methodology, possibly together with the use of subsampling techniques, is performed. Case studies in the fields of environment and finance will illustrate the performance of the new extremal index estimator comparatively to the classical one.