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here is the log from the commit of package octave-forge-nan for
openSUSE:Factory checked in at 2021-11-18 10:33:58
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/octave-forge-nan (Old)
and /work/SRC/openSUSE:Factory/.octave-forge-nan.new.1895 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "octave-forge-nan"
Thu Nov 18 10:33:58 2021 rev:14 rq:931972 version:3.6.1
Changes:
--------
--- /work/SRC/openSUSE:Factory/octave-forge-nan/octave-forge-nan.changes
2021-09-22 22:13:12.780335786 +0200
+++
/work/SRC/openSUSE:Factory/.octave-forge-nan.new.1895/octave-forge-nan.changes
2021-11-18 10:34:00.091916779 +0100
@@ -1,0 +2,8 @@
+Fri Nov 12 23:04:59 UTC 2021 - Atri Bhattacharya <[email protected]>
+
+- Update to version 3.6.1:
+ * signrank: update computation of p-value according to revised
+ references, and validated against R.
+ * cdfplot: use histo instead of histo_mex.
+
+-------------------------------------------------------------------
Old:
----
nan-3.6.0.tar.gz
New:
----
nan-3.6.1.tar.gz
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ octave-forge-nan.spec ++++++
--- /var/tmp/diff_new_pack.6q2LQe/_old 2021-11-18 10:34:00.523917181 +0100
+++ /var/tmp/diff_new_pack.6q2LQe/_new 2021-11-18 10:34:00.527917184 +0100
@@ -18,7 +18,7 @@
%define octpkg nan
Name: octave-forge-%{octpkg}
-Version: 3.6.0
+Version: 3.6.1
Release: 0
Summary: A statistics and machine learning toolbox
License: GPL-3.0-or-later
++++++ nan-3.6.0.tar.gz -> nan-3.6.1.tar.gz ++++++
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/nan-3.6.0/DESCRIPTION new/nan-3.6.1/DESCRIPTION
--- old/nan-3.6.0/DESCRIPTION 2021-07-26 16:19:19.000000000 +0200
+++ new/nan-3.6.1/DESCRIPTION 2021-11-03 21:09:44.000000000 +0100
@@ -1,6 +1,6 @@
Name: NaN
-Version: 3.6.0
-Date: 2021-07-26
+Version: 3.6.1
+Date: 2021-11-03
Author: Alois Schl??gl <[email protected]>
Maintainer: Alois Schl??gl
Title: The NaN-toolbox
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/nan-3.6.0/NEWS new/nan-3.6.1/NEWS
--- old/nan-3.6.0/NEWS 2021-07-26 16:19:19.000000000 +0200
+++ new/nan-3.6.1/NEWS 2021-11-03 21:09:44.000000000 +0100
@@ -1,3 +1,12 @@
+
+2021-11-03: Release of NaN-toolbox 3.6.1
+
+* signrank: update computation of p-value
+ according to revised references,
+ and validated against R.
+* cdfplot: use histo instead of histo_mex
+
+
2021-07-26: Release of NaN-toolbox 3.6.0
* corrplot, knnsearch <NEW>
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/nan-3.6.0/inst/cdfplot.m new/nan-3.6.1/inst/cdfplot.m
--- old/nan-3.6.0/inst/cdfplot.m 2021-07-26 16:19:19.000000000 +0200
+++ new/nan-3.6.1/inst/cdfplot.m 2021-11-03 21:09:44.000000000 +0100
@@ -40,7 +40,7 @@
% Foundation, Inc., 51 Franklin Street - Fifth Floor, Boston, MA 02110-1301,
USA.
-his = histo_mex(X(:));
+his = histo(X(:));
cdf = cumsum(his.H,1) ./ sum(his.H,1);
ix1 = ceil ([1:2*size(his.X,1)]'/2);
ix2 = floor([2:2*size(his.X,1)]'/2);
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/nan-3.6.0/inst/signrank.m
new/nan-3.6.1/inst/signrank.m
--- old/nan-3.6.0/inst/signrank.m 2021-07-26 16:19:19.000000000 +0200
+++ new/nan-3.6.1/inst/signrank.m 2021-11-03 21:09:44.000000000 +0100
@@ -1,50 +1,50 @@
function [pval, h, stats] = signrank (x, m, alpha, tail, DIM)
% SIGNRANK - Wilcoxon signed-rank test
-% The Wilcoxon signed-rank test is a non-parametric statistical hypothesis
-% test used to compare two related samples whether their population median
-% ranks differ [1-3]. SIGNRANK treads NaNs as "Missing values" and ignores
these.
-% Octave's statistical package has also wilcoxon_test, however, this works
only
-% for data with N>25 samples, signrank is based on the works [1-3] and can
-% be used also for smaller sample sizes.
-%
-% pval = signrank(x,m)
-% tests Null-hypothesis that median of x is m.
-% pval = signrank(x,y)
-% size of x and size of y must match, it is tested whether the
-% difference x-y is significantly different to m=0;
+% The Wilcoxon signed-rank test is a non-parametric statistical hypothesis
+% test used to compare two related samples whether their population median
+% ranks differ [1-4]. SIGNRANK treads NaNs as "Missing values" and ignores
these.
+% The current implementation has been validated against wilcox.test of R
(v4.0.4).
+%
+% pval = signrank(X,m [, ...])
+% tests Null-hypothesis that median of x is m.
+% size(m,DIM) must be one, all other dimensions must match those of X
+% pval = signrank(x,y [, ...])
+% size of x and size of y must match, it is tested whether the
+% difference x-y is significantly different to m=0;
% pval = signrank(x,y,alpha)
% pval = signrank(x,y,alpha,tail)
% pval = signrank(x,y,alpha,tail,DIM)
% [pval,H,stats] = signrank(...)
%
-% H=1 indicates a rejection of the Null-hypothesis at a significance
-% level of alpha (default alpha = 0.05).
-%
+% H=1 indicates a rejection of the Null-hypothesis at a significance
+% level of alpha (default alpha = 0.05).
+%
% With the optional argument string TAIL, the alternative of interest
% can be selected. If TAIL is '!=' or '<>' or 'both', the null is tested
% against the two-sided Alternative `mean (X) ~= mean (Y)'. If TAIL
% is '>' or 'right', the one-sided Alternative `mean (X) > mean (Y)' is
used.
% Similarly for '<' or 'left', the one-sided Alternative `mean (X) < mean
% (Y)' is used. The default is the two-sided case.
-%
-% H returns whether the Null-Hypotheses must be rejected.
-% The p-value of the test is returned in PVAL.
-%
-% signrank works on the first non-singleton dimension or on DIM.
+%
+% H returns whether the Null-Hypotheses must be rejected.
+% The p-value of the test is returned in PVAL.
+%
+% signrank works on the first non-singleton dimension of X and Y, or on
DIM.
%
% If no output argument is given, the p-value of the test is
% displayed.
%
-% Reference(s):
+% Reference(s):
% [1] Glenn A Walker, (2002)
-% Common Statistical Methods for Clinical Research (with SAS examples),
2nd edition
+% Common Statistical Methods for Clinical Research (with SAS examples),
2nd edition
% Chapter 12 The Wilcoxon Signed-Rank Test.
% [2] https://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test
% [3]
https://math.stackexchange.com/questions/1414794/wilcoxon-signed-rank-test
+% [4] https://de.wikipedia.org/wiki/Wilcoxon-Vorzeichen-Rang-Test
-% Copyright (C) 2010,2019 by Alois Schloegl <[email protected]>
-% This function is part of the NaN-toolbox
-% http://pub.ist.ac.at/~schloegl/matlab/NaN/
+% Copyright (C) 2010,2019,2021 by Alois Schloegl <[email protected]>
+% This function is part of the NaN-toolbox
+% http://pub.ist.ac.at/~schloegl/matlab/NaN/
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
@@ -73,7 +73,10 @@
if (nargin < 4) || isempty(tail)
tail = '~=';
end
- if (~ ischar (tail))
+ if (~isnumeric(alpha))
+ error ('signrank: alpha must be numeric');
+ end
+ if (~ischar(tail))
error ('signrank: tail must be a string');
end
if nargin<5,
@@ -81,74 +84,143 @@
end;
if isempty(DIM), DIM=1; end;
- szx = size(x);
- szm = size(m);
- szx(DIM) = 1;
+ szx = size(x);
+ szm = size(m);
+ szx(DIM) = 1;
szm(DIM) = 1;
if size(m,DIM)==1
- ;
+ x = x-repmat(m,size(x)./szx);
elseif size(x,DIM) == size(m,DIM)
x = x-m;
m = zeros(szm);
else
- error ('signrank: dimension of X and Y do not fit');
- end
-
- % Algorithm according to
- % https://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test
-
- % Step 2: exclude 0, and get N_r
- x(abs(x)==0)=NaN;
- Nr=sum(~isnan(x),DIM);
+ error ('signrank: dimension of X and Y do not fit');
+ end
+
+ % Algorithm using "signed rank procedure" [2]
+ x(x==0)=NaN;
+ Nr=sum(~isnan(x) & (x~=0), DIM);
- % Step 3 and 4: Order and Rank the data
- Rix = tiedrank(abs(x));
+ % Order and Rank the data using "modified ranks" [2]
+ Rix = tiedrank(abs(x), DIM);
- % Glenn A Walker [3]
- % compute correction for ties;
+ % Glenn A Walker [3,4]: compute correction for ties;
sz = size(x);
P = [DIM,1:DIM-1,DIM+1:length(sz)];
- HIS = histo2(reshape(permute(Rix,P),sz(DIM),sz([1:DIM-1,DIM+1:end])));
- m = HIS.H;
+ HIS = histo2(reshape(permute(Rix,P),sz(DIM),prod(sz([1:DIM-1,DIM+1:end]))));
+ m = HIS.H;
m(HIS.H<=1) = NaN;
C =
ipermute(reshape(sumskipnan(m.*(m-1).*(m+1),1),[1,sz([1:DIM-1,DIM+1:end])]),P);
- %Step 5:
- W = sum(sign(x).*Rix,DIM);
- % z = W./sqrt(Nr.*(Nr+1).*(2*Nr+1)./(6*(Nr-1)));
+ W = sumskipnan(sign(x).*Rix,DIM);
+ z = W./sqrt(Nr.*(Nr+1).*(2*Nr+1)/6 - C/12);
+ p2 = 2*abs(W)./(Nr.*Nr);
% https://math.stackexchange.com/questions/1414794/wilcoxon-signed-rank-test
- Tplus = sumskipnan((x>0).*Rix, DIM);
- Tminus = sumskipnan((x<0).*Rix, DIM);
+ Tplus = sumskipnan((x>0) .* Rix, DIM);
+ Tminus = sumskipnan((x<0) .* Rix, DIM);
- stats.z = (max(Tplus,Tminus)-Nr.*(Nr+1)/4)./sqrt(Nr.*(Nr+1).*(2*Nr+1)./24);
- stats.signedrank = max(Tplus,Tminus);
-
- S = (Tplus - Tminus) / 2;
- V = (Nr.* (Nr+1).*(2*Nr+1) - C/2) / 24;
- t = S .* sqrt(max(Nr-1,0)) ./ sqrt(Nr.*V - S.*S);
- cdf = tcdf(t, Nr);
+ stats.signedrank = min(Tplus, Tminus);
+ #
+ # simple formula is:
+ # z = (Tplus - Nr.*(Nr+1)/4)./sqrt(Nr.*(Nr+1).*(2*Nr+1)/24);
+ # but for approximation for N<60, and ties (see [4])
+ # z = (abs(Tplus - Nr.*(Nr+1)/4)-0.5)./sqrt(Nr.*(Nr+1).*(2*Nr+1)/24 -
C/48);
+ V = sqrt(Nr.*(Nr+1).*(2*Nr+1)./24 - C/48);
+
+ stats.z = z;
+ % effective size [2]
+ stats.r = 2*(Tplus-Tminus)./(Nr.*(Nr+1));
- % see also NaN/ttest
+ % see also NaN/ttest
if (strcmp (tail, '~=') || strcmp (tail, '!=') || strcmp (tail, '<>')) ||
strcmp(tail,'both'),
+ z = -(abs(Tplus - Nr.*(Nr+1)/4) - .5) ./ V;
+ cdf = normcdf(z);
pval = 2 * min (cdf, 1 - cdf);
elseif strcmp (tail, '>') || strcmp(tail,'right'),
- pval = 1 - cdf;
+ z = -(Tplus - Nr.*(Nr+1)/4 - .5) ./ V;
+ pval = normcdf(z);
elseif strcmp (tail, '<') || strcmp(tail,'left'),
- pval = cdf;
+ z = -(Tminus - Nr.*(Nr+1)/4 - .5) ./ V;
+ pval = normcdf(z);
else
error ('signrank: option %s not recognized', tail);
end
- h = pval < alpha;
+ h = pval < alpha;
if (nargout == 0)
fprintf(1,' pval: %g\n', pval);
end
- stats.t=t;
%!test
-%! % example from [3]
-%! x =
[15,8;10,3;6,7;5,13;10,2;15,12;7,14;5,8;8,13;12,3;4,9;13,3;8,10;10,2;11,4;13,7;6,1;6,11;,9,3;
5,5;10,2;9,8;11,5;8,8];
+%! x =
[15,8;10,3;6,7;5,13;10,2;15,12;7,14;5,8;8,13;12,3;4,9;13,3;8,10;10,2;11,4;13,7;6,1;6,11;,9,3;
5,5;10,2;9,8;11,5;8,8];
%! [p,h,stats] = signrank( x(:,1), x(:,2) );
-%! assert ( abs(stats.t - 2.184) < .01)
+%! assert ( abs(p - 0.045350) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([1:15]',8);
+%! assert ( h==0 )
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]',25);
+%! assert ( abs(p - 0.005793) < 1e-5)
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]',25,[],'<');
+%! assert ( abs(p - 2.8965e-03) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]', 25, [], '>');
+%! assert ( abs(p - 0.9979) < 1e-5)
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]', 19);
+%! assert ( abs(p - 0.838) < 1e-4)
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]', 19, [], '<');
+%! assert ( abs(p - 0.6204) < 1e-4)
+%!
+%!test
+%! [p,h,stats]=signrank([17.6, 20.6, 22.2, 15.3, 20.9, 21.0, 18.9, 18.9, 18.9,
18.2]', 19, [], '>');
+%! assert ( abs(p - 0.419) < 1e-4)
+%!
+%!test
+%! [p,h,stats]=signrank([0, 2, 3, 4, 6, 7, 8, 9, 11, 14, 15, 17, -18]+1,1);
+%! assert ( abs(p - 0.037633) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([0, 2, 3, 4, 6, 7, 8, 9, 11, 14, 15, 17, -18],0);
+%! assert ( abs(p - 0.037633) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([ 2, 3, 4, 6, 7, 8, 9, 11, 14, 15, 17, -18],0);
+%! assert ( abs(p - 0.037633) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([-1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,-13],0);
+%! assert ( abs(p - 0.030276) < 1e-6)
+%!
+%!test
+%! [p,h,stats]=signrank([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, -12],0);
+%! assert ( abs(p - 0.037633) < 1e-6)
+%!
+%!test
+%! x = [125 110;115 122;130 125;140 120;140 140;115 124;140 123;125 137;140
135;135 145];
+%! [p,h,stats] = signrank( x(:,1), x(:,2) );
+%%! assert ( abs(p - 0.6113) < 1e-4) % this does not match [2]
+%! assert ( abs(p - 0.6353) < 1e-4) % matches the result in R
+%!
+%!test
+%! x = [4 1;3 2; 2 3; 5 0; 5 0; 3 2];
+%! [p,h,stats] = signrank( x(:,1), x(:,2) );
+%!
+%!test
+%! SZ = [100,5,3]; X=round(rand(SZ)*10); Y=round(rand(SZ)*10);
+%! p1 = signrank(X,Y,1,[],1);
+%! assert(size(p1,2)==SZ(2) && size(p1,3)==SZ(3))
+%! p2 = signrank(X,Y,1,[],2);
+%! assert(size(p2,1)==SZ(1) && size(p2,3)==SZ(3))
+%! p3 = signrank(X,Y,1,[],3);
+%! assert(size(p3,2)==SZ(2) && size(p3,1)==SZ(1))
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn'
'--exclude=.svnignore' old/nan-3.6.0/inst/tiedrank.m
new/nan-3.6.1/inst/tiedrank.m
--- old/nan-3.6.0/inst/tiedrank.m 2021-07-26 16:19:19.000000000 +0200
+++ new/nan-3.6.1/inst/tiedrank.m 2021-11-03 21:09:44.000000000 +0100
@@ -1,15 +1,14 @@
-function R=tiedrank(X,flag1,flag2)
+function R = tiedrank(X, DIM)
% TIEDRANK compute rank of samples, the mean value is used in case of ties
% this function is just a wrapper for RANKS, and provided for compatibility
% with the statistics toolbox of matlab(tm)
%
-% R = tiedrank(X)
+% R = tiedrank(X [,DIM] )
% computes the rank R of vector X
%
% see also: RANKS
-
-% Copyright (C) 2009,2010,2017 by Alois Schloegl
<[email protected]>
+% Copyright (C) 2009,2010,2017,2021 by Alois Schloegl
<[email protected]>
% This function is part of the NaN-toolbox
% http://pub.ist.ac.at/~schloegl/matlab/NaN/
@@ -27,28 +26,18 @@
% along with this program; If not, see <http://www.gnu.org/licenses/>.
-if nargin>3,
+if nargin>2,
error('more than 3 input argument is currently not supported ')
-end;
-if nargin<2,
- flag1=0;
end;
-if nargin<3,
- flag2=0;
-end;
-
-if nargout>2,
- warning('more than 1 output argument is currently not supported ')
-end;
if nargin<2,
DIM = [];
end;
if isempty(DIM),
- DIM = find(size(X)>1,1);
+ DIM = find(size(X)>1, 1);
if isempty(DIM), DIM = 1; end;
end
if (DIM<1), DIM = 1; end; %% Hack, because min([])=0 for FreeMat v3.5
-R = ranks(X,DIM);
+R = ranks(X,DIM);
