calculates histogram for multiple columns with separate bin values for each data column.
R=nan_histo2(Y) R = nan_histo2(Y, W)
data
weight vector containing weights of each sample, number of rows of Y and W must match. default W=[] indicates that each sample is weighted with 1.
is a struct with th fields
the bin-values, bin-values are computed separately for each data column, thus R.X is a matrix, each column contains the the bin values of for each data column, unused elements are indicated with NaN. In order to have common bin values, use nan_histo3.
is the frequency of occurence of value X
are the number of valid (not NaN) samples (i.e. sum of weights)
more histogram-based results can be obtained by hist2res2
C.E. Shannon and W. Weaver "The mathematical theory of communication" University of Illinois Press, Urbana 1949 (reprint 1963).