Zobrazeno 1 - 10
of 400
pro vyhledávání: '"Cook, Dianne"'
Studying the Performance of the Jellyfish Search Optimiser for the Application of Projection Pursuit
The projection pursuit (PP) guided tour interactively optimises a criteria function known as the PP index, to explore high-dimensional data by revealing interesting projections. The optimisation in PP can be non-trivial, involving non-smooth function
Externí odkaz:
http://arxiv.org/abs/2407.13663
Indexes are useful for summarizing multivariate information into single metrics for monitoring, communicating, and decision-making. While most work has focused on defining new indexes for specific purposes, more attention needs to be directed towards
Externí odkaz:
http://arxiv.org/abs/2401.05812
The woylier package implements tour interpolation paths between frames using Givens rotations. This provides an alternative to the geodesic interpolation between planes currently available in the tourr package. Tours are used to visualise high-dimens
Externí odkaz:
http://arxiv.org/abs/2311.08181
This paper proposes a spatiotemporal clustering algorithm and its implementation in the R package spotoroo. This work is motivated by the catastrophic bushfires in Australia throughout the summer of 2019-2020 and made possible by the availability of
Externí odkaz:
http://arxiv.org/abs/2308.10505
Regression experts consistently recommend plotting residuals for model diagnosis, despite the availability of many numerical hypothesis test procedures designed to use residuals to assess problems with a model fit. Here we provide evidence for why th
Externí odkaz:
http://arxiv.org/abs/2308.05964
Publikováno v:
Journal of Computational and Graphical Statistics, 33(3):1118-1121, 2024
The usual goal of supervised learning is to find the best model, the one that optimizes a particular performance measure. However, what if the explanation provided by this model is completely different from another model and different again from anot
Externí odkaz:
http://arxiv.org/abs/2302.13356
Principal component analysis is a long-standing go-to method for exploring multivariate data. The principal components are linear combinations of the original variables, ordered by descending variance. The first few components typically provide a goo
Externí odkaz:
http://arxiv.org/abs/2301.00077
This paper describes new user controls for examining high-dimensional data using low-dimensional linear projections and slices. A user can interactively change the contribution of a given variable to a low-dimensional projection, which is useful for
Externí odkaz:
http://arxiv.org/abs/2210.05228
Textbook data is essential for teaching statistics and data science methods because they are clean, allowing the instructor to focus on methodology. Ideally textbook data sets are refreshed regularly, especially when they are subsets taken from an on
Externí odkaz:
http://arxiv.org/abs/2205.06417