A study on simplified principal component analysis
| dc.contributor.advisor | Hooda, B.K. | |
| dc.contributor.author | Kamlesh | |
| dc.date.accessioned | 2016-11-17T10:36:48Z | |
| dc.date.available | 2016-11-17T10:36:48Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | Principal component analysis though deduces dimensionality of the data, it suffers from the draw back that the each component is a linear combination of all the original variables and one has to interpret the result in terms of all the original variables. In the present study various techniques for obtaining simplified components have been described and critically reviewed. Best linear predictor (BLP) and corrected sum of variances (CSV) criterion have also been presented for determining the optimality of simple components with respect to the PCA which is considered the optimal solution. Simplified principal components simulated and real data sets were obtained through varimax rotation and as well as using simple component analysis algorithm proposed by Rousson and Gasser (2004) worked out compared with the ordinary principal components both in term of simplicity and optimality. | en_US |
| dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/86038 | |
| dc.language.iso | en | en_US |
| dc.publisher | CCSHAU | en_US |
| dc.sub | Statistics | |
| dc.subject | Statistical methods, Sets, Selection, Developmental stages, Solutes, Biological phenomena, Physical control, Byproducts, Accounts, Planting | en_US |
| dc.these.type | M.Sc | |
| dc.title | A study on simplified principal component analysis | en_US |
| dc.type | Thesis | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- CCSHAU-291588-Kamlesh.pdf
- Size:
- 2.82 MB
- Format:
- Adobe Portable Document Format
- Description:
- A study on simplified principal component analysis
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 2.28 KB
- Format:
- Item-specific license agreed upon to submission
- Description: