We address the classification problem where an item is declared to be from population ? j if certain of its characteristics v are assumed to be sampled from the distribution with pdf f j (v | % j ), where j=1, 2, ..., m. We first solve the two population classification problem and then extend the re
A bayesian decision approach to model monitoring and cusums
โ Scribed by P. J. Harrison; P. P. Veerapen
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 463 KB
- Volume
- 13
- Category
- Article
- ISSN
- 0277-6693
No coin nor oath required. For personal study only.
โฆ Synopsis
Abstract
Cumulative Sum techniques are widely used in quality control and model monitoring. A singleโsided cusum may be regarded essentially as a sequence of sequential tests which, in many cases, such as those for the Exponential Family, is equivalent to a Sequence of Sequential Probability Ratio Tests. The relationship between cusums and Bayesian decisions is difficult to establish using conventional methods. An alternative approach is proposed which not only reveals a relation but also offers a very simple formulation of the decision process involved in model monitoring. This is first illustrated for a Normal mean and then extended to other important practical cases including Dynamic Models. For Vโmask cusum graphs a particular feature is the interpretation of the distance of the V vertex from the latest plotted point in terms of the prior precision as measured in โequivalentโ observations.
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