Skew-t Information Matrix: Evaluation and Use

dc.contributor.advisor	Douglas, Martin R
dc.contributor.author	Uthaisaad, Chindhanai
dc.date.accessioned	2018-04-24T22:17:08Z
dc.date.issued	2018-04-24
dc.date.submitted	2018
dc.description	Thesis (Master's)--University of Washington, 2018
dc.description.abstract	Azzalini’s skew-t distributions, described in detail in Azzalini [2013], have become very popular because of their practical usefulness and the complete R package sn for skew-normal distributions that include extensive support for fitting and analysis of skew-t distributions. A major difficulty is that the skew-t distribution expected information matrix has no analytical form. This thesis develops an R package skewtInfo to compute the expected information matrix through numerical integrations and investigates the accuracy of the resulting matrix and its use for computing finite-sample approximations for skew-t parameter estimates.
dc.embargo.lift	2019-04-24T22:17:08Z
dc.embargo.terms	Restrict to UW for 1 year -- then make Open Access
dc.format.mimetype	application/pdf
dc.identifier.other	Uthaisaad_washington_0250O_18223.pdf
dc.identifier.uri	http://hdl.handle.net/1773/41733
dc.language.iso	en_US
dc.rights	CC BY-NC-SA
dc.subject	information matrix
dc.subject	maximum penalized likelihood estimator
dc.subject	skew-t distribution
dc.subject	Statistics
dc.subject	Finance
dc.subject.other	Applied mathematics
dc.title	Skew-t Information Matrix: Evaluation and Use
dc.type	Thesis

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