dc.contributor.author | Tofallis, C. | |
dc.date.accessioned | 2007-10-15T13:06:01Z | |
dc.date.available | 2007-10-15T13:06:01Z | |
dc.date.issued | 1999 | |
dc.identifier.citation | Tofallis , C 1999 , ' Model building with multiple dependent variables and constraints ' , Journal of the Royal Statistical Society: Series D (The Statistician) , vol. 48 , no. 3 , pp. 371-378 . | |
dc.identifier.issn | 0039-0526 | |
dc.identifier.other | dspace: 2299/919 | |
dc.identifier.other | ORCID: /0000-0001-6150-0218/work/34655913 | |
dc.identifier.uri | http://hdl.handle.net/2299/919 | |
dc.description.abstract | The most widely used method for finding relationships between several quantities is multiple regression. This however is restricted to a single dependent variable. We present a more general method which allows models to be constructed with multiple variables on both sides of an equation and which can be computed easily using a spreadsheet program. The underlying principle (originating from canonical correlation analysis) is that of maximising the correlation between the two sides of the model equation. This paper presents a fitting procedure which makes it possible to force the estimated--model to satisfy constraint conditions which it is required to possess, these may arise from--theory, prior knowledge or be intuitively obvious. We also show that the least squares approach--to the problem is inadequate as it produces models which are not scale invariant. | en |
dc.format.extent | 42034 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of the Royal Statistical Society: Series D (The Statistician) | |
dc.title | Model building with multiple dependent variables and constraints | en |
dc.contributor.institution | Department of Marketing and Enterprise | |
dc.description.status | Peer reviewed | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |