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On Selecting Parametric Link Transformation Families in Generalized Linear Models
| Content Provider | Semantic Scholar |
|---|---|
| Author | Czado, Claudia |
| Copyright Year | 1995 |
| Abstract | The use of parametric link transformation families in generalized linear models (GLM) has been shown to improve substantially the t of standard analyses using a xed link in some data sets (see Czado 1993], for example). When link and regression parameters are globally orthogonal (Cox and Reid 1987]), then the variance innation of the regression parameter estimates due to the additional estimation of the link is asymptotically zero. Parameter orthogonality also induces numerical stability which is seen in the reduction of computation time required for the calculation of parameter estimates. This stability remains a desirable property even for inferences which are conditional on a xed link value. Czado and Santner 1992b] for binomial error and Czado 1992] for GLM's have shown that only local orthogonality can be achieved in general. This paper provides conditions on the link family to extend the notion of local orthogonality at a point to orthogonality in a neighborhood asymptotically and shows that the resulting links are location and scale invariant. General concepts for the construction of such links are given, and it is shown how they relate to link families proposed in the literature. The ideas are illustrated by two examples. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://math.yorku.ca/Who/Faculty/Czado/select.ps |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Arabic numeral 0 Computation (action) Estimated Generalized linear model Numerical stability Population Parameter Sample Variance Time complexity |
| Content Type | Text |
| Resource Type | Article |
