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20112020
most citedA data-based power transformation for compositional data

36 citations · 36 across the 3 of their papers we have counts for

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5 papers · 1 filter

stat.ME2020

Non-parametric regression for networks

Katie E. Severn, Ian L. Dryden, Simon P. Preston

Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian ma…

stat.ME2019

Manifold valued data analysis of samples of networks, with applications in corpus linguistics

Katie E. Severn, Ian L. Dryden, Simon P. Preston

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical ana…

stat.ME2017

The extended power distribution: A new distribution on

Chibueze E. Ogbonnaya, Simon P. Preston, Andrew T. A. Wood

We propose a two-parameter bounded probability distribution called the extended power distribution. This distribution on is similar to the beta distribution, however there…

stat.ME2015

Improved classification for compositional data using the -transformation

Michail Tsagris, Simon Preston, Andrew T. A. Wood

In compositional data analysis an observation is a vector containing non-negative values, only the relative sizes of which are considered to be of interest. Without loss of general…

stat.ME201136 cited

A data-based power transformation for compositional data

Michail T. Tsagris, Simon Preston, Andrew T. A. Wood

Compositional data analysis is carried out either by neglecting the compositional constraint and applying standard multivariate data analysis, or by transforming the data using the…