quickcode (version 1.2.0)

pairDist: Calculate the distance of points from the center of a cluster

Description

This function operates on multivariate data and calculates the distance of points from the centroid of one or more clusters.

Usage

pairDist(data, scale = FALSE, roundit = NULL)

Arguments

data

data frame object or a matrix/array object

scale

Boolean used for scaling the dataset

roundit

Round x number of decimal places; min value is 0; max value is 6

Function utility

Used to generate the computations needed to model pair-distance measures in three dimensions

More information about this function

The pairDist function is used to quantify how far each data point (row) is from the overall mean across all columns. It’s commonly used in multivariate statistics, machine learning, and data analysis to assess the variability or similarity of data points relative to their mean. More specifically, the function is used in outlier detection and cluster analysis to evaluate the dispersion of data. Used in conjunction with other calculations, pairDist output can also be used to model data in three dimensions.

References

the current function was adapted from one of the examples in the svgViewR package,
https://cran.r-project.org/web/packages/svgViewR/svgViewR.pdf

Examples

data(airquality)
airq <- airquality[, 1:4]

# example 1:
x <- pairDist(airq, roundit = 3)

# example 2:
y <- pairDist(airq, scale = TRUE, roundit = 5)

# example 3

data <- matrix(
  c(1, 5, NA, 4, 5, 6, NA, 8, 9, NA, 12, 23, 6, 0, 3, 3, 8, 15),
  ncol = 3,
  byrow = TRUE
)

dist <- pairDist(data, roundit = 2)
dist_scaled <- pairDist(data, scale = TRUE, roundit = 6)