sim.field.network.stats
Class CentralizationStatistics

java.lang.Object
  extended by sim.field.network.stats.CentralizationStatistics

public class CentralizationStatistics
extends java.lang.Object


Constructor Summary
CentralizationStatistics(Network network, FreemanNodeIndex metric)
           
CentralizationStatistics(Network network, NodeIndex metric)
           
 
Method Summary
 double getCentralizationIndexMean(boolean useNormalization)
          The average node centrality is Group Centralization for metrics like Information Centralization (Wasserman and Faust, page 197), Proximity Prestige (Wasserman and Faust, page 204), etc.
 double getCentralizationIndexVariance(boolean useNormalization, boolean unbiased)
           
 double getGeneralCentralizationIndex()
          Computes Freeman's General Centralization Index (Wasserman and Faust, page 177)
static Bag getGraphTheoreticCenter(Network network)
          Identifies the points with the smallest maximal distance to all other points.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

CentralizationStatistics

public CentralizationStatistics(Network network,
                                NodeIndex metric)

CentralizationStatistics

public CentralizationStatistics(Network network,
                                FreemanNodeIndex metric)
Method Detail

getCentralizationIndexMean

public double getCentralizationIndexMean(boolean useNormalization)
The average node centrality is Group Centralization for metrics like


getCentralizationIndexVariance

public double getCentralizationIndexVariance(boolean useNormalization,
                                             boolean unbiased)
Parameters:
unbiased - according to (Wasserman and Faust, page 180), the sum of (avg - val_i)^2 should be diveded by n. I also offer the unbiased variance (i.e. dividing by n-1).

getGraphTheoreticCenter

public static Bag getGraphTheoreticCenter(Network network)
Identifies the points with the smallest maximal distance to all other points.


getGeneralCentralizationIndex

public double getGeneralCentralizationIndex()
Computes Freeman's General Centralization Index (Wasserman and Faust, page 177)