## Abstract We consider asymptotic behavior of selfโnormalized sums of autoregressive fractionally integrated moving average (ARFIMA) processes whose innovations are GARCH errors. The asymptotic distribution of the sums is derived under very mild conditions. Applications to unit root tests with ARF
Group testing in presence of classification errors
โ Scribed by Diwakar Gupta; Regina Malina
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 143 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
No coin nor oath required. For personal study only.
โฆ Synopsis
We modify Dorfman's and Sterrett's group testing protocols to make them suitable for testing blood samples for the presence of HIV antibodies, as well as for many industrial applications, when false negatives cannot be tolerated. We รฟrst propose that test kit sensitivity be increased to nearly 100 per cent by altering the reactive versus non-reactive threshold. Subsequently, group and repeat testing are used with a careful selection of group size and the number of times a test is repeated, in order to maximize e ciency while keeping the false positive predictive value (FPPV) within a speciรฟed limit. Numerical calculations show that our testing protocol is e cient, has low procedural complexity and keeps both types of classiรฟcation errors below speciรฟed tolerance limits.
๐ SIMILAR VOLUMES
We consider tests for the equality of prediction mean squared errors and for forecast encompassing. It is shown that, if forecast errors exhibit ARCH, size distortions are induced in the usual tests. Adjusted test statistics are suggested to alleviate this problem.
In this paper we investigate the properties of the Lagrange Multiplier [LM] test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely aected if AOs