File: fn_empdfsort.m

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function imfcnt = fn_empdfsort(imfcnt,imf_h,imfloor,hbin,ninv)
% imfcnt = fn_empdfsort(imfcnt,imf_h,imfloor,hbin,ninv)
%    Variablewise (but multivariate) empirical probability distribution with counts
%       sorted into bins variablewise
%    Note that since a particular draw (imf_h) can be below "imfloor" and above "imceiling"
%       (=(imceiling-imfloor)*hbin), this function allows ninv+2 bins for each variable
%
% imfcnt:  initial ninv+2-by-k matrix that records counts in each bin given a column in imfcnt
%          if k==1, then only one variable is considered.
% imf_h:  k-element vector of particular draws.  Need not be a 1-by-k row vector.
% imfloor: k-element vector of low values of imf but imf_h can be below "imfloor" and above "imceiling"
% hbin:  k-element vector of bin lengths = (imceilling-imfloor)/ninv.
% ninv:  number of bins between "imfloor" and "imceiling"
%------------------
% imfcnt:  updated ninv+2-by-k matrix of counts (probability)
%
% January 1999 TZ; Revised, August 2000.
%
% Copyright (C) 1997-2012 Tao Zha
%
% This free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% It is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
%
% If you did not received a copy of the GNU General Public License
% with this software, see <http://www.gnu.org/licenses/>.
%


%** find the bin locations and arrange them to the order of 1, 2, ...
imf_h=imf_h(:); imfloor=imfloor(:); hbin=hbin(:);
countInt = floor( (imf_h-imfloor) ./ hbin ); % k-by-1
       % bin locations from <0, 0, 1,..., ninv-1, >=ninv, a total of ninv+2 bins
countInt = 2+countInt';  % 1-by-k row vector, see my shock (1), pp.1
                    % move everyting by 2 so as to take account of <0

countInt(find(countInt<2)) = 1;     % set <0 or -infinity at 1 to start
countInt(find(countInt>=ninv+2)) = ninv+2;  % set >=ninv+2 or +infinity at ninv+2 to end
countInt = countInt + (0:length(countInt)-1)*(ninv+2);
             % 1-by-k*(ninv+2) index vector to fill the matrix with prob. (counts)
             % The term after "+" implies that with every count, we skip ninv+2 to keep
             %    each column in "imfcnt" with only one element (which is probability)
imfcnt(countInt) = imfcnt(countInt) + 1;