cities {psychTools}

R Documentation

Distances between 11 US cities

Description

Airline distances between 11 US cities may be used as an example for multidimensional scaling or cluster analysis.

Usage

data(cities)

Format

A data frame with 11 observations on the following 11 variables.

ATL

Atlana, Georgia

BOS

Boston, Massachusetts

ORD

Chicago, Illinois

DCA

Washington, District of Columbia

DEN

Denver, Colorado

LAX

Los Angeles, California

MIA

Miami, Florida

JFK

New York, New York

SEA

Seattle, Washington

SFO

San Francisco, California

MSY

New Orleans, Lousianna

Details

An 11 x11 matrix of distances between major US airports. This is a useful demonstration of multiple dimensional scaling.

city.location is a dataframe of longitude and latitude for those cities.

Note that the 2 dimensional MDS solution does not perfectly capture the data from these city distances. Boston, New York and Washington, D.C. are located slightly too far west, and Seattle and LA are slightly too far south.

Source

https://www.timeanddate.com/worldclock/distance.html

Examples

data(cities)
city.location[,1] <- -city.location[,1] #included in the cities data set
plot(city.location, xlab="Dimension 1", ylab="Dimension 2",
   main ="Multidimensional scaling of US cities")
#do the mds   
city.loc <- cmdscale(cities, k=2) #ask for a 2 dimensional solution  round(city.loc,0) 
city.loc <- -city.loc  #flip the axes
 city.loc <- psych::rescale(city.loc,apply(city.location,2,mean),apply(city.location,2,sd))
points(city.loc,type="n") #add the date point to the map
text(city.loc,labels=names(cities))

## Not run:    #we need the maps package to be available
#an overlay map can be added if the package maps is available
if(require(maps)) {
  map("usa",add=TRUE)
}

## End(Not run)

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