3 research outputs found
Conditional Visualisation for Statistical Models
It is difficult to understand data and statistical models in high-dimensional space.
One way to approach the problem is conditional visualisation, but methods in this
area have lagged behind the considerable advances in statistical modelling in recent
decades. This thesis presents a new approach to conditional visualisation which
uses interactive computer graphics, and supports the exploration of a broad range
of statistical models.
The new approach to conditional visualisation consists of visualising a single lowdimensional
section at a time, showing fitted models on the section, and enhancing
the section by displaying observed data which are near the section according to a
similarity measure. Two ways of choosing sections are given |choosing sections
interactively using data summary graphics, and choosing sections programmatically
according to some criteria.
The visualisations in this thesis necessitate interactive graphics, which are implemented
in the condvis package in R