L1.meas {cem} | R Documentation |
Evaluates L1 distance between multidimensional histograms
L1.meas(group, data, drop=NULL, breaks = NULL, weights)
group |
the group variable |
data |
the data |
drop |
a vector of variable names in the data frame to ignore |
breaks |
a list of vectors of cutpoints; if not specified, automatic choice will be made |
weights |
weights |
This function calculates the L1 distance on the k-dimensional histogram.
If breaks
is not specified, the Scott automated bin calculation
is used (which coarsens less than Sturges, which used in
cem
). Please refer to cem
help page. In
this case, breaks are used to calculate the L1 measure.
If breaks
is missing, the default rule to calculate cutpoints
is the Scott's rule.
This code also calculate the Local Common Support (LCS) measure, which is the proportion of non empty k-dimensional cells of the histogram which contain at least one observation per group.
An object of class L1.meas
which is a list with the following fields
L1 |
The numerical value of the L1 measure |
breaks |
A list of cutpoints used to calculate the L1 measure |
LCS |
The numerical value of the Local Common Support proportion |
Stefano Iacus, Gary King, and Giuseppe Porro
Stefano Iacus, Gary King, Giuseppe Porro, ``Matching for Casual Inference Without Balance Checking,'' http://gking.harvard.edu/files/abs/cem-abs.shtml
data(LL) L1.meas(LL$treated,LL, drop=c("treated","re78"))