All functions 


Compresses a data matrix based on mutual information (segregation) 

Calculate Dissimilarity Index 

Calculate expected values when true segregation is zero 

Calculates the entropy of a distribution 

Calculates pairwise exposure 

Create crosswalk after compression 

Adjustment of marginal distributions using iterative proportional fitting 

Calculates isolation 

Turns a contingency table into long format 

merge_units 

Decomposes the difference between two M indices 

Calculate expected values when true segregation is zero 

Calculates local segregation indices based on M 

Calculate total segregation for M and H 

Calculate a nested decomposition of segregation for M and H 

Calculate detailed withincategory segregation scores for M and H 

Studentlevel data including SES status 

Ethnic/racial composition of schools for 2000/2001 

Ethnic/racial composition of schools for 2005/2006 

Scree plot for segregation compression 

A visual representation of twogroup segregation 

A visual representation of segregation 

segregation: Entropybased segregation indices 