Towards the geometry of model sensitivity: an Illustration

Karim Anaya-Izquierdo, Frank Critchley, Paul Marriott, Paul Vos

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In statistical practice model building, sensitivity and uncertainty are major concerns of the analyst. This paper looks at these issues from an information geometric point of view. Here, we define sensitivity to mean understanding how inference about a problem of interest changes with perturbations of the model. In particular it is an example of what we call computational information geometry. The embedding of simple models in much larger information geometric spaces is shown to illuminate these critically important issues.
Original languageEnglish
Title of host publicationComputational Information Geometry
Subtitle of host publicationFor Image and Signal Processing
EditorsFrank Nielsen, Kit Dodson, Frank Critchley
PublisherSpringer
Pages33-62
ISBN (Electronic)9783319470580
ISBN (Print)9783319470566
DOIs
Publication statusPublished - 2017

Publication series

NameSignals and Communication Technology

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  • Cite this

    Anaya-Izquierdo, K., Critchley, F., Marriott, P., & Vos, P. (2017). Towards the geometry of model sensitivity: an Illustration. In F. Nielsen, K. Dodson, & F. Critchley (Eds.), Computational Information Geometry : For Image and Signal Processing (pp. 33-62). (Signals and Communication Technology). Springer. https://doi.org/10.1007/978-3-319-47058-0_2