Common structure in panels of short time series
Typically, in many studies in ecology, epidemiology, biomedicine and others, we are confronted with panels of short time–series of which we are interested in obtaining a biologically meaningful grouping. Here, we propose a bootstrap approach to test whether the regression functions or the variances of the error terms in a family of stochastic regression models are the same. Our general setting includes panels of time–series models as a special case. We rigorously justify the use of the test by investigating its asymptotic properties, both theoretically and through simulations. The latter confirm that for finite sample size, bootstrap provides a better approximation than classical asymptotic theory.We then apply the proposed tests to the mink–muskrat data across 81 trapping regions in Canada. Ecologically interpretable groupings are obtained, which serve as a necessary first step before a fuller biological and statistical analysis of the food chain interaction.
| Item Type | Article |
|---|---|
| Keywords | bootstrap,Canadian mink-muskrat data,nonlinear time-series,predator-prey interactions,similarity measure,threshold modelling |
| Departments | Statistics |
| DOI | 10.1098/rspb.2000.1306 |
| Date Deposited | 02 Jul 2008 11:05 |
| URI | https://researchonline.lse.ac.uk/id/eprint/6325 |