Stochastically Independent Components in the Analysis of Variance
✍ Scribed by Dr. T. Drwięga
- Publisher
- John Wiley and Sons
- Year
- 1982
- Tongue
- English
- Weight
- 471 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
Independent component analysis (ICA), which separates fMRI data into spatially independent patterns of activity, has recently been shown to be a suitable method for exploratory fMRI analysis. The validity of the assumptions of ICA, mainly that the underlying components are spatially independent and
Variance component methods are now being used in linkage analysis to detect genes influencing complex diseases. These methods are easily extended to allow for simultaneous estimation of both the additive effects of multiple loci on phenotypic variation (conditional oligogenic analysis) and the addit
## Abstract Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene‐wise mixed model analysis. As thousands of genes are available, it is desirable to combine inform