๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Predictive modeling of pharmaceutical processes with missing and noisy data

โœ 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

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Finite sample prediction and interpolati
โœ Jeremy Penzer; Brian Shea ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 133 KB

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

Analogue and Numerical Modelling of Sedi
Multivariate modelling of the pharmaceut
โœ Johan A. Westerhuis; Pierre M. J. Coenegracht ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 133 KB ๐Ÿ‘ 2 views

The pharmaceutical process of wet granulation and tableting is described as a two-step process. Besides the process variables of both steps and the composition variables of the powder mixture, the physical properties of the intermediate granules are also used to model the crushing strength and disin

Joint modelling of longitudinal and time
โœ Michael J. Sweeting; Simon G. Thompson ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 353 KB ๐Ÿ‘ 2 views

## Abstract Shared random effects joint models are becoming increasingly popular for investigating the relationship between longitudinal and timeโ€toโ€event data. Although appealing, such complex models are computationally intensive, and quick, approximate methods may provide a reasonable alternative

Solidification and Crystallization (HERL
โœ Herlach, Dieter M. ๐Ÿ“‚ Article ๐Ÿ“… 2005 ๐Ÿ› Wiley-VCH Verlag GmbH & Co. KGaA ๐ŸŒ German โš– 132 KB ๐Ÿ‘ 1 views

current Interest In Research Of Solidification Of Melts Is Focused To Understand Crystal Nucleation And Crystal Growth. They Determine The Solidified Product With Its Physical Properties. A Detailed Description Of These Processes Lead To The Development And Validation Of Physical Models, Which May F