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A brief synopsis of progress in diierential geometry in statistics is followed by a note of some points of tension in the developing relationship between these disciplines. The preferred point nature of much of statistics is described and suggests the adoption of a corresponding geometry which reduces these tensions. Applications of preferred point geometry… (More)

Di¤erential geometry has found fruitful application in statistical inference. In particular, Amari's (1990) expected geometry is used in higher order asymptotic analysis, and in the study of su¢ciency and ancillarity. However, we can see three drawbacks to the use of a di¤erential geometric approach in econometrics and statistics more generally. Firstly,… (More)

A new class of local mixture models called local scale mixture models is introduced here. This class is particularly suitable for the analysis of mixtures of the negative exponential distribution. The affine structure revealed by specific asymptotic expansions is the motivation for the construction of these models. They are shown to have very nice… (More)

Exponential families and the related exponential dispersion models are the workhorses of parametric modelling theory. One reason for their popularity is their associated inference theory which is very clean both from a theoretical and a computational point of view. One way in which this set of tools can be enriched in a natural and interpretable way is… (More)

This whitepaper is designed to provide a basic understanding of the main concepts of the DO-254 compliance specification for electronic component design. It outlines the major steps involved in a DO-254 compliant ASIC/FPGA design and verification process, and explains how differentiating tool features can be mapped to enhance and facilitate critical stages… (More)

We introduce a new approach to goodness-of-fit testing in the high dimensional, sparse extended multinomial context. The paper takes a computational information geometric approach, extending classical higher order asymptotic theory. We show why the Wald – equivalently , the Pearson χ 2 and score statistics – are unworkable in this context, but that the… (More)