Density Functions and Descriptive Statistics for Distance Measures in Cartesian Space

This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for these shapes. The shapes are in the unit line, the unit square, unit circle, unit sphere and unit triangle. In all instances, an exact, symbolic solution is sought, but there are four occasions where that is not possible—for these cases, a reasonable approximate solution is obtained. For each distance measure, mean, median and standard deviation measures are provided as well.

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Publication Details

Journal
American Journal of Operations Research
Published
2025-01-01
DOI
https://doi.org/10.4236/ajor.2025.155008
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
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article

Density Functions and Descriptive Statistics for Distance Measures in Cartesian Space

Patrick R. McMullen
American Journal of Operations Research
Bayesian Methods and Mixture Models
article

Density Functions and Descriptive Statistics for Distance Measures in Cartesian Space

Patrick R. McMullen
article en

Abstract

This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for these shapes. The shapes are in the unit line, the unit square, unit circle, unit sphere and unit triangle. In all instances, an exact, symbolic solution is sought, but there are four occasions where that is not possible—for these cases, a reasonable approximate solution is obtained. For each distance measure, mean, median and standard deviation measures are provided as well.

American Journal of Operations ResearchVol. 15(05)
Wake Forest University (US)
Openalex Percentile: Top 88%
Bayesian Methods and Mixture Models
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