Function reference

dissimilarity()
 Calculates Index of Dissimilarity

exposure()
 Calculates pairwise exposure indices

isolation()
 Calculates isolation indices

mutual_total()
 Calculates the Mutual Information Index M and Theil's Entropy Index H

mutual_total_nested()
 Calculates a nested decomposition of segregation for M and H

mutual_within()
 Calculates detailed withincategory segregation scores for M and H

mutual_local()
 Calculates local segregation scores based on M

segcurve()
 A visual representation of twogroup segregation

segplot()
 A visual representation of segregation

mutual_expected()
 Calculates expected values when true segregation is zero

dissimilarity_expected()
 Calculates expected values when true segregation is zero

mutual_difference()
 Decomposes the difference between two M indices

ipf()
 Adjustment of marginal distributions using iterative proportional fitting

compress()
 Compresses a data matrix based on mutual information (segregation)

merge_units()
 Creates a compressed dataset

get_crosswalk()
 Create crosswalk after compression

scree_plot()
 Scree plot for segregation compression

school_ses
 Studentlevel data including SES status

schools00
 Ethnic/racial composition of schools for 2000/2001

schools05
 Ethnic/racial composition of schools for 2005/2006

entropy()
 Calculates the entropy of a distribution

matrix_to_long()
 Turns a contingency table into long format