A transformation which allows Cholesky decomposition to be used to evaluate the exact likelihood function of an ARIMA model with missing data has recently been suggested. This method is extended to allow calculation of ยฎnite sample predictions of future observations. The output from the exact likeli
Predictive modeling of pharmaceutical processes with missing and noisy data
โ Scribed by Fani Boukouvala; Fernando J. Muzzio; Marianthi G. Ierapetritou
- Publisher
- American Institute of Chemical Engineers
- Year
- 2010
- Tongue
- English
- Weight
- 816 KB
- Volume
- 56
- Category
- Article
- ISSN
- 0001-1541
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