Abstract
Abstract. In this paper, we investigate the use of asymptotic theory to design and control simulation experiments concerning the finite sample properties of test statistics. The tests considered in the Monte Carlo experiments are various diagnostic checks which have been proposed for assessing the adequacy of the specification of open‐loop transfer function models. Attention is focussed on both the empirical size and power of the testing procedures examined and a simple descriptive measure of the relative performance of alternative tests based on changes in power resulting from variations in significance level is suggested. Whilst asymptotic theoretic considerations determine the parameter values selected, it is seen that useful information as to the actual small sample behaviour of the tests can be obtained by employing a direct modification to the standard theory.
Original language | English |
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Pages (from-to) | 263-277 |
Number of pages | 15 |
Journal | Journal of Time Series Analysis |
Volume | 2 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Jan 1981 |
Externally published | Yes |
Keywords
- Analysis of simulations
- Diagnostic testing
- Experimental design
- Local alternative
- Transfer function model