Design Issues for Generalized Linear Models: A Review

摘要: Generalized linear models (GLMs) have been used quite effectively in the modeling of a mean response under nonstandard conditions, where discrete as well continuous data distributions can be accommodated. The choice design for GLM is very important task development and building an adequate model. However, one major problem that handicaps construction its dependence on unknown parameters fitted Several approaches proposed past 25 years to solve this problem. These approaches, however, provided only partial solutions apply some special cases, problem, general, remains largely unresolved. purpose article focus attention aforementioned We provide survey various existing techniques dealing with This includes discussions concerning locally optimal designs, sequential Bayesian designs quantile dispersion graph approach comparing GLMs.