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Data for The correlation space of Gaussian latent tree models and model selection without fitting

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Knight, Chris G. (2016) Data for The correlation space of Gaussian latent tree models and model selection without fitting. [Dataset]

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yeastdata.zip - Other
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Abstract

We provide a complete description of possible distributions consistent with any Gaussian latent tree model. This description consists of polynomial equations and inequalities involving covariances between the observed variables. Testing inequality constraints can be done using the inverse Wishart distribution and this leads to simple preliminary assessment of tree-compatibility. To test equality constraints we employ general techniques of tetrad analyses. This approach is effective even for small sample sizes and can be easily adjusted to test either entire models or just particular macrostructures of a tree. Our methods are simple to implement and do not require fitting of the model. The versatility of the techniques is illustrated by performing exploratory and confirmatory tetrad analyses in linguistic and biological settings respectively.

Item Type: Dataset
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Type of Data: Growth data for 7 species of yeast in 96 different environments
Library of Congress Subject Headings (LCSH): Gaussian distribution, Latent variables
Publisher: Statistics, University of Warwick
Official Date: 28 July 2016
Dates:
DateEvent
28 July 2016Published
3 June 2016Accepted
Status: Not Peer Reviewed
Publication Status: Published
Media of Output: TXT files in zip file
Access rights to Published version: Open Access
Copyright Holders: Please contact Chris.Knight@manchester.ac.uk
Description:

Optical density of yeast species when observed in various environments.

Key:

‘grotreatment’ is one of 96 environments, ‘pretreatment’ is ‘None’ in all cases, ‘Well’ indicates the spatial layout, ‘time_h' is hours of growth and ‘value’ is the optical density (which has a different baseline for each environment).

RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
ES/I90427/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/K021672/2[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
PIOF-GA-2011-300975Seventh Framework Programmehttp://dx.doi.org/10.13039/100011102
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  • Related item in WRAP
Contributors:
ContributionNameContributor ID
AuthorShiers, N. L.UNSPECIFIED
AuthorZwiernik, PiotrUNSPECIFIED
AuthorAston, John A. D.26103
AuthorSmith, J. Q.UNSPECIFIED

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