22 citations · 127 across the 26 of their papers we have counts for
27 papers
A Plot is Worth a Thousand Tests: Assessing Residual Diagnostics with the Lineup Protocol
Weihao Li, Dianne Cook, Emi Tanaka +1
Regression experts consistently recommend plotting residuals for model diagnosis, despite the availability of many numerical hypothesis test procedures designed to use residuals to…
A Study on a User-Controlled Radial Tour for Variable Importance in High-Dimensional Data
Nicholas Spyrison, Dianne Cook, Kim Marriott
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…
New and simplified manual controls for projection and slice tours, with application to exploring classification boundaries in high dimensions
Ursula Laa, Alex Aumann, Dianne Cook +1
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 Journey from Wild to Textbook Data to Reproducibly Refresh the Wages Data from the National Longitudinal Survey of Youth Database
Dewi Amaliah, Dianne Cook, Emi Tanaka +2
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…
Exploring Local Explanations of Nonlinear Models Using Animated Linear Projections
Nicholas Spyrison, Dianne Cook, Przemyslaw Biecek
The increased predictive power of machine learning models comes at the cost of increased complexity and loss of interpretability, particularly in comparison to parametric statistic…
cubble: An R Package for Organizing and Wrangling Multivariate Spatio-temporal Data
H. Sherry Zhang, Dianne Cook, Ursula Laa +2
Multivariate spatio-temporal data refers to multiple measurements taken across space and time. For many analyses, spatial and time components can be separately studied: for example…