Scatter plots are effective diagrams to visualize distributions, clusters and correlations in two-dimensional data space. For highdimensional data, scatter plot matrices can be formed to show all two-dimensional combinations of dimensions. Several previous approaches for exploration of large scatter plot spaces have focused on ranking and sorting scatter plot matrices based on global patterns. ...

The use of the least squares method to calculate the best-fitting line through a two-dimensional scatter plot typically requires the user to assume that one of the variables depends on the other. However, in many cases the relationship between the two variables is more complex, and it is not valid to say that one variable is independent and the other is dependent. When analysing such data resea...

In this article a numerical MATLAB algorithm is presented to visualize the workspace of serial and parallel kinematics. For serial kinematics the Monte Carlo Method is used to convert the inputted DH-Parameters to a scatter plot of the reachable workspace. The article gives also a detailed insight into the processing of these scatter plot to find and visualize the boundary points of the workspa...

Scatter plot is a useful method for visualising clusters and outliers in continuous data. However, this method cannot be used directly on nominal data due to a lack of natural ordering and 'distance' in nominal values. One solution to this problem is to map the multi-dimensional nominal data to a numeric space, and then draw a scatter plot of the data points based on the first two principal com...

Computer-assisted interactive visualization has become a valuable tool for discovering the underlying meaning of tabular data, including categorical tabular data. The capabilities of the more traditionally mundane kinds of pictures like scatter plots can be expanded to usefully depict categorical tabular data by incorporating annotations and transforms, and by integrating the extensions into an...

Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model models the distribution in a high dimensional shape space, where each shape is represented by a single point. We present a design study on the intuitive exploration and visualization of shape spaces and shape models. Our ...

DOI: 10.1002/sscp.202200033 The cover picture has beef cattle and pigs in a farm environment overlaid with snapshot of three-dimensional scatter plot that contains the following inlaid pictures; pork samples been prepared for volatile extraction, gas chromatograph mass spectrometer, undertaking chromatography olfactory analysis two-dimensional chromatograph.

Many data sets are high dimensional. It has been a common practice to use lower dimensional linear projections of the data for visual inspection. The lower dimension is usually 1 or 2 (or maybe 3). More precisely, if X 1 ; : : :; X n 2 IR p are p-dimensional data, then a k (< p)-dimensional linear projection is Z 1 ; : : : ; Z n 2 IR k where Z i = T X i for some p k matrix such that T = I k , t...