Function reference • segregation

All functions
`compress()`	Compresses a data matrix based on mutual information (segregation)
`dissimilarity()`	Calculate Dissimilarity Index
`dissimilarity_expected()`	Calculate expected values when true segregation is zero
`entropy()`	Calculates the entropy of a distribution
`exposure()`	Calculates pairwise exposure
`get_crosswalk()`	Create crosswalk after compression
`ipf()`	Adjustment of marginal distributions using iterative proportional fitting
`isolation()`	Calculates isolation
`matrix_to_long()`	Turns a contingency table into long format
`merge_units()`	merge_units
`mutual_difference()`	Decomposes the difference between two M indices
`mutual_expected()`	Calculate expected values when true segregation is zero
`mutual_local()`	Calculates local segregation indices based on M
`mutual_total()`	Calculate total segregation for M and H
`mutual_total_nested()`	Calculate a nested decomposition of segregation for M and H
`mutual_within()`	Calculate detailed within-category segregation scores for M and H
`school_ses`	Student-level data including SES status
`schools00`	Ethnic/racial composition of schools for 2000/2001
`schools05`	Ethnic/racial composition of schools for 2005/2006
`scree_plot()`	Scree plot for segregation compression
`segcurve()`	A visual representation of two-group segregation
`segplot()`	A visual representation of segregation
`segregation`	segregation: Entropy-based segregation indices

Reference