Abstract
A simple class of generalized sequential likelihood ratio tests is introduced for testing hypotheses in multivariate exponential families. These sequential tests have asymptotically optimal frequentist properties and also provide approximate Bayes solutions with respect to a large class of prior distributions. 1? Introduction. Let X\,X2,- ? ? be i.i.d. ? ? 1 random vectors whose common multivariate density (with respect to some nondegenerate dominating measure v) belongs to the exponential family
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