Bump minimal required Octave version to 4.4
Sébastien Villemot
parent
fd99f4fee8
commit
4e314a529b
|
|
@ -187,12 +187,6 @@ Copyright: 2013-2019 Ben Abbott
|
|||
2019 Dynare Team
|
||||
License: GPL-3+
|
||||
|
||||
Files: matlab/missing/corrcoef/corrcoef.m matlab/missing/corrcoef/sumskipnan.m
|
||||
matlab/missing/corrcoef/flag_implicit_skip_nan.m matlab/missing/corrcoef/tcdf.m
|
||||
Copyright: 2000-2005,2008,2009,2011 by Alois Schloegl <alois.schloegl@gmail.com>
|
||||
2014 Dynare Team
|
||||
License: GPL-3+
|
||||
|
||||
Files: matlab/lmmcp/catstruct.m
|
||||
Copyright: 2005 Jos van der Geest <jos@jasen.nl>
|
||||
2013 Christophe Gouel
|
||||
|
|
|
|||
|
|
@ -78,14 +78,14 @@ if isoctave
|
|||
'of precompiled mex files and some\nfeatures, like solution ' ...
|
||||
'of models approximated at third order, will not be available.'], supported_octave_version())
|
||||
skipline()
|
||||
elseif octave_ver_less_than('4.2') % Should match the test in mex/build/octave/configure.ac
|
||||
% and in m4/ax_mexopts.m4
|
||||
elseif octave_ver_less_than('4.4') % Should match the test in mex/build/octave/configure.ac
|
||||
skipline()
|
||||
warning(['This version of Dynare has only been tested on Octave 4.2 and above. Dynare may fail to run or give unexpected result. Consider upgrading your version of Octave.'])
|
||||
warning(['This version of Dynare has only been tested on Octave 4.4 and above. Dynare may fail to run or give unexpected result. Consider upgrading your version of Octave.'])
|
||||
skipline()
|
||||
end
|
||||
else
|
||||
if matlab_ver_less_than('7.9') % Should match the test in mex/build/matlab/configure.ac
|
||||
% and in m4/ax_mexopts.m4
|
||||
skipline()
|
||||
warning('This version of Dynare has only been tested on MATLAB 7.9 (R2009b) and above. Since your MATLAB version is older than that, Dynare may fail to run, or give unexpected results. Consider upgrading your MATLAB installation, or switch to Octave.');
|
||||
skipline()
|
||||
|
|
|
|||
|
|
@ -86,11 +86,6 @@ if isoctave && octave_ver_less_than('5')
|
|||
p{end+1} = '/missing/ordeig';
|
||||
end
|
||||
|
||||
% corrcoef with two outputs is missing in Octave < 4.4 (ticket #796)
|
||||
if isoctave && octave_ver_less_than('4.4') && ~user_has_octave_forge_package('nan')
|
||||
p{end+1} = '/missing/corrcoef';
|
||||
end
|
||||
|
||||
%% intersect(…, 'stable') doesn't exist in Octave and in MATLAB < R2013a
|
||||
if isoctave || matlab_ver_less_than('8.1')
|
||||
p{end+1} = '/missing/intersect_stable';
|
||||
|
|
@ -98,10 +93,10 @@ end
|
|||
|
||||
% Replacements for functions of the MATLAB statistics toolbox
|
||||
if isoctave
|
||||
% These functions were part of Octave < 4.4, they are now in the statistics Forge package
|
||||
if ~octave_ver_less_than('4.4') && ~user_has_octave_forge_package('statistics')
|
||||
% Our replacement functions don't work under Octave (because of gamrnd, see
|
||||
% #1638), hence the statistics toolbox is now a hard requirement
|
||||
% Under Octave, these functions are in the statistics Forge package.
|
||||
% Our replacement functions don't work under Octave (because of gamrnd, see
|
||||
% #1638), hence the statistics toolbox is now a hard requirement
|
||||
if ~user_has_octave_forge_package('statistics')
|
||||
error('You must install the "statistics" package from Octave Forge, either with your distribution package manager or with "pkg install -forge statistics"')
|
||||
end
|
||||
else
|
||||
|
|
|
|||
|
|
@ -1,385 +0,0 @@
|
|||
function [R,sig,ci1,ci2,nan_sig] = corrcoef(X,Y,varargin)
|
||||
% CORRCOEF calculates the correlation matrix from pairwise correlations.
|
||||
% The input data can contain missing values encoded with NaN.
|
||||
% Missing data (NaN's) are handled by pairwise deletion [15].
|
||||
% In order to avoid possible pitfalls, use case-wise deletion or
|
||||
% or check the correlation of NaN's with your data (see below).
|
||||
% A significance test for testing the Hypothesis
|
||||
% 'correlation coefficient R is significantly different to zero'
|
||||
% is included.
|
||||
%
|
||||
% [...] = CORRCOEF(X);
|
||||
% calculates the (auto-)correlation matrix of X
|
||||
% [...] = CORRCOEF(X,Y);
|
||||
% calculates the crosscorrelation between X and Y
|
||||
%
|
||||
% [...] = CORRCOEF(..., Mode);
|
||||
% Mode='Pearson' or 'parametric' [default]
|
||||
% gives the correlation coefficient
|
||||
% also known as the 'product-moment coefficient of correlation'
|
||||
% or 'Pearson''s correlation' [1]
|
||||
% Mode='Spearman' gives 'Spearman''s Rank Correlation Coefficient'
|
||||
% This replaces SPEARMAN.M
|
||||
% Mode='Rank' gives a nonparametric Rank Correlation Coefficient
|
||||
% This is the "Spearman rank correlation with proper handling of ties"
|
||||
% This replaces RANKCORR.M
|
||||
%
|
||||
% [...] = CORRCOEF(..., param1, value1, param2, value2, ... );
|
||||
% param value
|
||||
% 'Mode' type of correlation
|
||||
% 'Pearson','parametric'
|
||||
% 'Spearman'
|
||||
% 'rank'
|
||||
% 'rows' how do deal with missing values encoded as NaN's.
|
||||
% 'complete': remove all rows with at least one NaN
|
||||
% 'pairwise': [default]
|
||||
% 'alpha' 0.01 : significance level to compute confidence interval
|
||||
%
|
||||
% [R,p,ci1,ci2,nansig] = CORRCOEF(...);
|
||||
% R is the correlation matrix
|
||||
% R(i,j) is the correlation coefficient r between X(:,i) and Y(:,j)
|
||||
% p gives the significance of R
|
||||
% It tests the null hypothesis that the product moment correlation coefficient is zero
|
||||
% using Student's t-test on the statistic t = r*sqrt(N-2)/sqrt(1-r^2)
|
||||
% where N is the number of samples (Statistics, M. Spiegel, Schaum series).
|
||||
% p > alpha: do not reject the Null hypothesis: 'R is zero'.
|
||||
% p < alpha: The alternative hypothesis 'R is larger than zero' is true with probability (1-alpha).
|
||||
% ci1 lower (1-alpha) confidence interval
|
||||
% ci2 upper (1-alpha) confidence interval
|
||||
% If no alpha is provided, the default alpha is 0.01. This can be changed with function flag_implicit_significance.
|
||||
% nan_sig p-value whether H0: 'NaN''s are not correlated' could be correct
|
||||
% if nan_sig < alpha, H1 ('NaNs are correlated') is very likely.
|
||||
%
|
||||
% The result is only valid if the occurence of NaN's is uncorrelated. In
|
||||
% order to avoid this pitfall, the correlation of NaN's should be checked
|
||||
% or case-wise deletion should be applied.
|
||||
% Case-Wise deletion can be implemented
|
||||
% ix = ~any(isnan([X,Y]),2);
|
||||
% [...] = CORRCOEF(X(ix,:),Y(ix,:),...);
|
||||
%
|
||||
% Correlation (non-random distribution) of NaN's can be checked with
|
||||
% [nan_R,nan_sig]=corrcoef(X,isnan(X))
|
||||
% or [nan_R,nan_sig]=corrcoef([X,Y],isnan([X,Y]))
|
||||
% or [R,p,ci1,ci2] = CORRCOEF(...);
|
||||
%
|
||||
% Further recommandation related to the correlation coefficient:
|
||||
% + LOOK AT THE SCATTERPLOTS to make sure that the relationship is linear
|
||||
% + Correlation is not causation because
|
||||
% it is not clear which parameter is 'cause' and which is 'effect' and
|
||||
% the observed correlation between two variables might be due to the action of other, unobserved variables.
|
||||
%
|
||||
% see also: SUMSKIPNAN, COVM, COV, COR, SPEARMAN, RANKCORR, RANKS,
|
||||
% PARTCORRCOEF, flag_implicit_significance
|
||||
%
|
||||
% REFERENCES:
|
||||
% on the correlation coefficient
|
||||
% [ 1] http://mathworld.wolfram.com/CorrelationCoefficient.html
|
||||
% [ 2] http://www.geography.btinternet.co.uk/spearman.htm
|
||||
% [ 3] Hogg, R. V. and Craig, A. T. Introduction to Mathematical Statistics, 5th ed. New York: Macmillan, pp. 338 and 400, 1995.
|
||||
% [ 4] Lehmann, E. L. and D'Abrera, H. J. M. Nonparametrics: Statistical Methods Based on Ranks, rev. ed. Englewood Cliffs, NJ: Prentice-Hall, pp. 292, 300, and 323, 1998.
|
||||
% [ 5] Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, pp. 634-637, 1992
|
||||
% [ 6] http://mathworld.wolfram.com/SpearmanRankCorrelationCoefficient.html
|
||||
% on the significance test of the correlation coefficient
|
||||
% [11] http://www.met.rdg.ac.uk/cag/STATS/corr.html
|
||||
% [12] http://www.janda.org/c10/Lectures/topic06/L24-significanceR.htm
|
||||
% [13] http://faculty.vassar.edu/lowry/ch4apx.html
|
||||
% [14] http://davidmlane.com/hyperstat/B134689.html
|
||||
% [15] http://www.statsoft.com/textbook/stbasic.html%Correlations
|
||||
% others
|
||||
% [20] http://www.tufts.edu/~gdallal/corr.htm
|
||||
% [21] Fisher transformation http://en.wikipedia.org/wiki/Fisher_transformation
|
||||
|
||||
% $Id: corrcoef.m 9387 2011-12-15 10:42:14Z schloegl $
|
||||
% Copyright (C) 2000-2004,2008,2009,2011 by Alois Schloegl <alois.schloegl@gmail.com>
|
||||
% Copyright (C) 2014-2017 Dynare Team
|
||||
% 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
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% This program 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.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
% Features:
|
||||
% + handles missing values (encoded as NaN's)
|
||||
% + pairwise deletion of missing data
|
||||
% + checks independence of missing values (NaNs)
|
||||
% + parametric and non-parametric (rank) correlation
|
||||
% + Pearson's correlation
|
||||
% + Spearman's rank correlation
|
||||
% + Rank correlation (non-parametric, Spearman rank correlation with proper handling of ties)
|
||||
% + is fast, using an efficient algorithm O(n.log(n)) for calculating the ranks
|
||||
% + significance test for null-hypthesis: r=0
|
||||
% + confidence interval included
|
||||
% - rank correlation works for cell arrays, too (no check for missing values).
|
||||
% + compatible with Octave and Matlab
|
||||
|
||||
global FLAG_NANS_OCCURED;
|
||||
|
||||
NARG = nargout; % needed because nargout is not reentrant in Octave, and corrcoef is recursive
|
||||
mode = [];
|
||||
|
||||
if nargin==1
|
||||
Y = [];
|
||||
Mode='Pearson';
|
||||
elseif nargin==0
|
||||
fprintf(2,'Error CORRCOEF: Missing argument(s)\n');
|
||||
elseif nargin>1
|
||||
if ischar(Y)
|
||||
varg = [Y,varargin];
|
||||
Y=[];
|
||||
else
|
||||
varg = varargin;
|
||||
end
|
||||
|
||||
if length(varg)<1
|
||||
Mode = 'Pearson';
|
||||
elseif length(varg)==1
|
||||
Mode = varg{1};
|
||||
else
|
||||
for k = 2:2:length(varg)
|
||||
mode = setfield(mode,lower(varg{k-1}),varg{k});
|
||||
end
|
||||
if isfield(mode,'mode')
|
||||
Mode = mode.mode;
|
||||
end
|
||||
end
|
||||
end
|
||||
if isempty(Mode), Mode='pearson'; end
|
||||
Mode=[Mode,' '];
|
||||
|
||||
|
||||
|
||||
FLAG_WARNING = warning; % save warning status
|
||||
warning('off');
|
||||
|
||||
[r1,c1]=size(X);
|
||||
if ~isempty(Y)
|
||||
[r2,c2]=size(Y);
|
||||
if r1~=r2
|
||||
fprintf(2,'Error CORRCOEF: X and Y must have the same number of observations (rows).\n');
|
||||
return
|
||||
end
|
||||
NN = real(~isnan(X)')*real(~isnan(Y));
|
||||
else
|
||||
[r2,c2]=size(X);
|
||||
NN = real(~isnan(X)')*real(~isnan(X));
|
||||
end
|
||||
|
||||
%%%%% generate combinations using indices for pairwise calculation of the correlation
|
||||
YESNAN = any(isnan(X(:))) | any(isnan(Y(:)));
|
||||
if YESNAN
|
||||
FLAG_NANS_OCCURED=(1==1);
|
||||
if isfield(mode,'rows')
|
||||
if strcmp(mode.rows,'complete')
|
||||
ix = ~any([X,Y],2);
|
||||
X = X(ix,:);
|
||||
if ~isempty(Y)
|
||||
Y = Y(ix,:);
|
||||
end
|
||||
YESNAN = 0;
|
||||
NN = size(X,1);
|
||||
elseif strcmp(mode.rows,'all')
|
||||
fprintf(1,'Warning: data contains NaNs, rows=pairwise is used.');
|
||||
%%NN(NN < size(X,1)) = NaN;
|
||||
elseif strcmp(mode.rows,'pairwise')
|
||||
%%% default
|
||||
end
|
||||
end
|
||||
end
|
||||
if isempty(Y)
|
||||
IX = ones(c1)-diag(ones(c1,1));
|
||||
[jx, jy ] = find(IX);
|
||||
[jxo,jyo] = find(IX);
|
||||
R = eye(c1);
|
||||
else
|
||||
IX = sparse([],[],[],c1+c2,c1+c2,c1*c2);
|
||||
IX(1:c1,c1+(1:c2)) = 1;
|
||||
[jx,jy] = find(IX);
|
||||
|
||||
IX = ones(c1,c2);
|
||||
[jxo,jyo] = find(IX);
|
||||
R = zeros(c1,c2);
|
||||
end
|
||||
|
||||
if strcmp(lower(Mode(1:7)),'pearson')
|
||||
% see http://mathworld.wolfram.com/CorrelationCoefficient.html
|
||||
if ~YESNAN
|
||||
[S,N,SSQ] = sumskipnan(X,1);
|
||||
if ~isempty(Y)
|
||||
[S2,N2,SSQ2] = sumskipnan(Y,1);
|
||||
CC = X'*Y;
|
||||
M1 = S./N;
|
||||
M2 = S2./N2;
|
||||
cc = CC./NN - M1'*M2;
|
||||
R = cc./sqrt((SSQ./N-M1.*M1)'*(SSQ2./N2-M2.*M2));
|
||||
else
|
||||
CC = X'*X;
|
||||
M = S./N;
|
||||
cc = CC./NN - M'*M;
|
||||
v = SSQ./N - M.*M; %max(N-1,0);
|
||||
R = cc./sqrt(v'*v);
|
||||
end
|
||||
else
|
||||
if ~isempty(Y)
|
||||
X = [X,Y];
|
||||
end
|
||||
for k = 1:length(jx)
|
||||
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
|
||||
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
|
||||
[s,n,s2] = sumskipnan(X(ik,[jx(k),jy(k)]),1);
|
||||
v = (s2-s.*s./n)./n;
|
||||
cc = X(ik,jx(k))'*X(ik,jy(k));
|
||||
cc = cc/n(1) - prod(s./n);
|
||||
%r(k) = cc./sqrt(prod(v));
|
||||
R(jxo(k),jyo(k)) = cc./sqrt(prod(v));
|
||||
end
|
||||
end
|
||||
|
||||
elseif strcmp(lower(Mode(1:4)),'rank')
|
||||
% see [ 6] http://mathworld.wolfram.com/SpearmanRankCorrelationCoefficient.html
|
||||
if ~YESNAN
|
||||
if isempty(Y)
|
||||
R = corrcoef(ranks(X));
|
||||
else
|
||||
R = corrcoef(ranks(X),ranks(Y));
|
||||
end
|
||||
else
|
||||
if ~isempty(Y)
|
||||
X = [X,Y];
|
||||
end
|
||||
for k = 1:length(jx)
|
||||
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
|
||||
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
|
||||
il = ranks(X(ik,[jx(k),jy(k)]));
|
||||
R(jxo(k),jyo(k)) = corrcoef(il(:,1),il(:,2));
|
||||
end
|
||||
X = ranks(X);
|
||||
end
|
||||
|
||||
elseif strcmp(lower(Mode(1:8)),'spearman')
|
||||
% see [ 6] http://mathworld.wolfram.com/SpearmanRankCorrelationCoefficient.html
|
||||
if ~isempty(Y)
|
||||
X = [X,Y];
|
||||
end
|
||||
|
||||
n = repmat(nan,c1,c2);
|
||||
|
||||
if ~YESNAN
|
||||
iy = ranks(X); % calculates ranks;
|
||||
|
||||
for k = 1:length(jx)
|
||||
[R(jxo(k),jyo(k)),n(jxo(k),jyo(k))] = sumskipnan((iy(:,jx(k)) - iy(:,jy(k))).^2); % NN is the number of non-missing values
|
||||
end
|
||||
else
|
||||
for k = 1:length(jx)
|
||||
%ik = ~any(isnan(X(:,[jx(k),jy(k)])),2);
|
||||
ik = ~isnan(X(:,jx(k))) & ~isnan(X(:,jy(k)));
|
||||
il = ranks(X(ik,[jx(k),jy(k)]));
|
||||
% NN is the number of non-missing values
|
||||
[R(jxo(k),jyo(k)),n(jxo(k),jyo(k))] = sumskipnan((il(:,1) - il(:,2)).^2);
|
||||
end
|
||||
X = ranks(X);
|
||||
end
|
||||
R = 1 - 6 * R ./ (n.*(n.*n-1));
|
||||
|
||||
elseif strcmp(lower(Mode(1:7)),'partial')
|
||||
fprintf(2,'Error CORRCOEF: use PARTCORRCOEF \n',Mode);
|
||||
|
||||
return
|
||||
|
||||
elseif strcmp(lower(Mode(1:7)),'kendall')
|
||||
fprintf(2,'Error CORRCOEF: mode ''%s'' not implemented yet.\n',Mode);
|
||||
|
||||
return
|
||||
else
|
||||
fprintf(2,'Error CORRCOEF: unknown mode ''%s''\n',Mode);
|
||||
end
|
||||
|
||||
if (NARG<2)
|
||||
warning(FLAG_WARNING); % restore warning status
|
||||
return
|
||||
end
|
||||
|
||||
|
||||
% CONFIDENCE INTERVAL
|
||||
if isfield(mode,'alpha')
|
||||
alpha = mode.alpha;
|
||||
elseif exist('flag_implicit_significance','file')
|
||||
alpha = flag_implicit_significance;
|
||||
else
|
||||
alpha = 0.01;
|
||||
end
|
||||
% fprintf(1,'CORRCOEF: confidence interval is based on alpha=%f\n',alpha);
|
||||
|
||||
|
||||
% SIGNIFICANCE TEST
|
||||
R(isnan(R))=0;
|
||||
tmp = 1 - R.*R;
|
||||
tmp(tmp<0) = 0; % prevent tmp<0 i.e. imag(t)~=0
|
||||
t = R.*sqrt(max(NN-2,0)./tmp);
|
||||
|
||||
if exist('t_cdf','file')
|
||||
sig = t_cdf(t,NN-2);
|
||||
elseif exist('tcdf','file')>1
|
||||
sig = tcdf(t,NN-2);
|
||||
else
|
||||
fprintf('CORRCOEF: significance test not completed because of missing TCDF-function\n')
|
||||
sig = repmat(nan,size(R));
|
||||
end
|
||||
sig = 2 * min(sig,1 - sig);
|
||||
|
||||
|
||||
if NARG<3
|
||||
warning(FLAG_WARNING); % restore warning status
|
||||
return
|
||||
end
|
||||
|
||||
|
||||
tmp = R;
|
||||
%tmp(ix1 | ix2) = nan; % avoid division-by-zero warning
|
||||
z = log((1+tmp)./(1-tmp))/2; % Fisher transformation [21]
|
||||
%sz = 1./sqrt(NN-3); % standard error of z
|
||||
sz = sqrt(2)*erfinv(1-alpha)./sqrt(NN-3); % confidence interval for alpha of z
|
||||
|
||||
ci1 = tanh(z-sz);
|
||||
ci2 = tanh(z+sz);
|
||||
|
||||
%ci1(isnan(ci1))=R(isnan(ci1)); % in case of isnan(ci), the interval limits are exactly the R value
|
||||
%ci2(isnan(ci2))=R(isnan(ci2));
|
||||
|
||||
if (NARG<5) || ~YESNAN
|
||||
nan_sig = repmat(NaN,size(R));
|
||||
warning(FLAG_WARNING); % restore warning status
|
||||
return
|
||||
end
|
||||
|
||||
%%%%% ----- check independence of NaNs (missing values) -----
|
||||
[nan_R, nan_sig] = corrcoef(X,double(isnan(X)));
|
||||
|
||||
% remove diagonal elements, because these have not any meaning %
|
||||
nan_sig(isnan(nan_R)) = nan;
|
||||
% remove diagonal elements, because these have not any meaning %
|
||||
nan_R(isnan(nan_R)) = 0;
|
||||
|
||||
if 0, any(nan_sig(:) < alpha)
|
||||
tmp = nan_sig(:); % Hack to skip NaN's in MIN(X)
|
||||
min_sig = min(tmp(~isnan(tmp))); % Necessary, because Octave returns NaN rather than min(X) for min(NaN,X)
|
||||
fprintf(1,'CORRCOFF Warning: Missing Values (i.e. NaNs) are not independent of data (p-value=%f)\n', min_sig);
|
||||
fprintf(1,' Its recommended to remove all samples (i.e. rows) with any missing value (NaN).\n');
|
||||
fprintf(1,' The null-hypotheses (NaNs are uncorrelated) is rejected for the following parameter pair(s).\n');
|
||||
[ix,iy] = find(nan_sig < alpha);
|
||||
disp([ix,iy])
|
||||
end
|
||||
|
||||
%%%%% ----- end of independence check ------
|
||||
|
||||
warning(FLAG_WARNING); % restore warning status
|
||||
|
|
@ -1,67 +0,0 @@
|
|||
function FLAG = flag_implicit_skip_nan(i)
|
||||
% FLAG_IMPLICIT_SKIP_NAN sets and gets default mode for handling NaNs
|
||||
% 1 skips NaN's (the default mode if no mode is set)
|
||||
% 0 NaNs are propagated; input NaN's give NaN's at the output
|
||||
%
|
||||
% FLAG = flag_implicit_skip_nan()
|
||||
% gets current mode
|
||||
%
|
||||
% flag_implicit_skip_nan(FLAG) % sets mode
|
||||
%
|
||||
% prevFLAG = flag_implicit_skip_nan(nextFLAG)
|
||||
% gets previous set FLAG and sets FLAG for the future
|
||||
% flag_implicit_skip_nan(prevFLAG)
|
||||
% resets FLAG to previous mode
|
||||
%
|
||||
% It is used in:
|
||||
% SUMSKIPNAN, MEDIAN, QUANTILES, TRIMEAN
|
||||
% and affects many other functions like:
|
||||
% CENTER, KURTOSIS, MAD, MEAN, MOMENT, RMS, SEM, SKEWNESS,
|
||||
% STATISTIC, STD, VAR, ZSCORE etc.
|
||||
%
|
||||
% The mode is stored in the global variable FLAG_implicit_skip_nan
|
||||
% It is recommended to use flag_implicit_skip_nan(1) as default and
|
||||
% flag_implicit_skip_nan(0) should be used for exceptional cases only.
|
||||
% This feature might disappear without further notice, so you should really not
|
||||
% rely on it.
|
||||
|
||||
|
||||
% 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
|
||||
% the Free Software Foundation; either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% This program 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.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with this program; if not, write to the Free Software
|
||||
% Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
|
||||
|
||||
% $Id: flag_implicit_skip_nan.m 8351 2011-06-24 17:35:07Z carandraug $
|
||||
|
||||
% Copyright (C) 2001-2003,2009 by Alois Schloegl <alois.schloegl@gmail.com>
|
||||
% Copyright (C) 2014-2017 Dynare Team
|
||||
%
|
||||
% This function is part of the NaN-toolbox
|
||||
% http://pub.ist.ac.at/~schloegl/matlab/NaN/
|
||||
|
||||
|
||||
persistent FLAG_implicit_skip_nan;
|
||||
|
||||
%% if strcmp(version,'3.6'), FLAG_implicit_skip_nan=(1==1); end; %% hack for the use with Freemat3.6
|
||||
|
||||
%%% set DEFAULT value of FLAG
|
||||
if isempty(FLAG_implicit_skip_nan)
|
||||
FLAG_implicit_skip_nan = (1==1); %logical(1); % logical.m not available on 2.0.16
|
||||
end
|
||||
|
||||
FLAG = FLAG_implicit_skip_nan;
|
||||
if nargin>0
|
||||
FLAG_implicit_skip_nan = (i~=0); %logical(i); %logical.m not available in 2.0.16
|
||||
if (~i)
|
||||
warning('flag_implicit_skipnan(0): You are warned!!! You have turned off skipping NaN in sumskipnan. This is not recommended. Make sure you really know what you do.')
|
||||
end
|
||||
end
|
||||
|
|
@ -1,192 +0,0 @@
|
|||
function [o,count,SSQ] = sumskipnan(x, DIM, W)
|
||||
% SUMSKIPNAN adds all non-NaN values.
|
||||
%
|
||||
% All NaN's are skipped; NaN's are considered as missing values.
|
||||
% SUMSKIPNAN of NaN's only gives O; and the number of valid elements is return.
|
||||
% SUMSKIPNAN is also the elementary function for calculating
|
||||
% various statistics (e.g. MEAN, STD, VAR, RMS, MEANSQ, SKEWNESS,
|
||||
% KURTOSIS, MOMENT, STATISTIC etc.) from data with missing values.
|
||||
% SUMSKIPNAN implements the DIMENSION-argument for data with missing values.
|
||||
% Also the second output argument return the number of valid elements (not NaNs)
|
||||
%
|
||||
% Y = sumskipnan(x [,DIM])
|
||||
% [Y,N,SSQ] = sumskipnan(x [,DIM])
|
||||
% [...] = sumskipnan(x, DIM, W)
|
||||
%
|
||||
% x input data
|
||||
% DIM dimension (default: [])
|
||||
% empty DIM sets DIM to first non singleton dimension
|
||||
% W weight vector for weighted sum, numel(W) must fit size(x,DIM)
|
||||
% Y resulting sum
|
||||
% N number of valid (not missing) elements
|
||||
% SSQ sum of squares
|
||||
%
|
||||
% the function FLAG_NANS_OCCURED() returns whether any value in x
|
||||
% is a not-a-number (NaN)
|
||||
%
|
||||
% features:
|
||||
% - can deal with NaN's (missing values)
|
||||
% - implements dimension argument.
|
||||
% - computes weighted sum
|
||||
% - compatible with Matlab and Octave
|
||||
%
|
||||
% see also: FLAG_NANS_OCCURED, SUM, NANSUM, MEAN, STD, VAR, RMS, MEANSQ,
|
||||
% SSQ, MOMENT, SKEWNESS, KURTOSIS, SEM
|
||||
|
||||
|
||||
% 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
|
||||
% the Free Software Foundation; either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% This program 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.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with this program; If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
% $Id: sumskipnan.m 9033 2011-11-08 20:58:07Z schloegl $
|
||||
%
|
||||
% Copyright (C) 2000-2005,2009,2011 by Alois Schloegl <alois.schloegl@gmail.com>
|
||||
% Copyright (C) 2014-2017 Dynare Team
|
||||
% This function is part of the NaN-toolbox
|
||||
% http://pub.ist.ac.at/~schloegl/matlab/NaN/
|
||||
|
||||
|
||||
global FLAG_NANS_OCCURED;
|
||||
|
||||
if nargin<2
|
||||
DIM = [];
|
||||
end
|
||||
if nargin<3
|
||||
W = [];
|
||||
end
|
||||
|
||||
% an efficient implementation in C of the following lines
|
||||
% could significantly increase performance
|
||||
% only one loop and only one check for isnan is needed
|
||||
% An MEX-Implementation is available in sumskipnan.cpp
|
||||
%
|
||||
% Outline of the algorithm:
|
||||
% for { k=1,o=0,count=0; k++; k<N}
|
||||
% if ~isnan(i(k))
|
||||
% { o += x(k);
|
||||
% count += 1;
|
||||
% tmp = x(k)*x(k)
|
||||
% o2 += tmp;
|
||||
% o3 += tmp.*tmp;
|
||||
% };
|
||||
|
||||
if isempty(DIM)
|
||||
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
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
% non-float data
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if (isempty(W) && (~(isa(x,'float') || isa(x,'double')))) || ~flag_implicit_skip_nan() %%% skip always NaN's
|
||||
if ~isempty(W)
|
||||
error('SUMSKIPNAN: weighted sum of integers not supported, yet');
|
||||
end
|
||||
x = double(x);
|
||||
o = sum(x,DIM);
|
||||
if nargout>1
|
||||
sz = size(x);
|
||||
N = sz(DIM);
|
||||
sz(DIM) = 1;
|
||||
count = repmat(N,sz);
|
||||
if nargout>2
|
||||
x = x.*x;
|
||||
SSQ = sum(x,DIM);
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
|
||||
if (length(size(x))<DIM)
|
||||
error('SUMSKIPNAN: DIM argument larger than number of dimensions of x');
|
||||
elseif ~isempty(W) && (size(x,DIM)~=numel(W))
|
||||
error('SUMSKIPNAN: size of weight vector does not match size(x,DIM)');
|
||||
end
|
||||
|
||||
%% mex and oct files expect double
|
||||
x = double(x);
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
% use Matlab-MEX function when available
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
%if 1,
|
||||
try
|
||||
|
||||
%% using sumskipnan_mex.mex
|
||||
|
||||
%% !!! hack: FLAG_NANS_OCCURED is an output argument, reserve memory !!!
|
||||
if isempty(FLAG_NANS_OCCURED)
|
||||
FLAG_NANS_OCCURED = logical(0); % default value
|
||||
end
|
||||
|
||||
if (nargout<2)
|
||||
o = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
if (~isreal(x))
|
||||
io = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
o = o + i*io;
|
||||
end
|
||||
return
|
||||
elseif (nargout==2)
|
||||
[o,count] = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
if (~isreal(x))
|
||||
[io,icount] = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
if any(count(:)-icount(:))
|
||||
error('Number of NaNs differ for REAL and IMAG part');
|
||||
else
|
||||
o = o+i*io;
|
||||
end
|
||||
end
|
||||
return
|
||||
elseif (nargout>=3)
|
||||
[o,count,SSQ] = sumskipnan_mex(real(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
if (~isreal(x))
|
||||
[io,icount,iSSQ] = sumskipnan_mex(imag(x),DIM,FLAG_NANS_OCCURED,W);
|
||||
if any(count(:)-icount(:))
|
||||
error('Number of NaNs differ for REAL and IMAG part');
|
||||
else
|
||||
o = o+i*io;
|
||||
SSQ = SSQ+iSSQ;
|
||||
end
|
||||
end
|
||||
return
|
||||
end
|
||||
end
|
||||
|
||||
if ~isempty(W)
|
||||
error('weighted sumskipnan requires sumskipnan_mex');
|
||||
end
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
% count non-NaN's
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
if nargout>1
|
||||
count = sum(x==x,DIM);
|
||||
FLAG_NANS_OCCURED = any(count(:)<size(x,DIM));
|
||||
end
|
||||
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
% replace NaN's with zero
|
||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
x(x~=x) = 0;
|
||||
o = sum(x,DIM);
|
||||
|
||||
if nargout>2
|
||||
x = real(x).^2 + imag(x).^2;
|
||||
SSQ = sum(x,DIM);
|
||||
end
|
||||
|
||||
%!assert(sumskipnan([1,2],1),[1,2])
|
||||
%!assert(sumskipnan([1,NaN],2),1)
|
||||
%!assert(sumskipnan([1,NaN],2),1)
|
||||
%!assert(sumskipnan([nan,1,4,5]),10)
|
||||
%!assert(sumskipnan([nan,1,4,5]',1,[3;2;1;0]),6)
|
||||
|
|
@ -1,64 +0,0 @@
|
|||
function p = tcdf(x,n)
|
||||
% TCDF returns student cumulative distribtion function
|
||||
%
|
||||
% cdf = tcdf(x,DF);
|
||||
%
|
||||
% Computes the CDF of the students distribution
|
||||
% with DF degrees of freedom
|
||||
% x,DF must be matrices of same size, or any one can be a scalar.
|
||||
%
|
||||
% see also: NORMCDF, TPDF, TINV
|
||||
|
||||
% Reference(s):
|
||||
|
||||
% $Id: tcdf.m 9033 2011-11-08 20:58:07Z schloegl $
|
||||
|
||||
% Copyright (C) 2000-2003,2009 by Alois Schloegl <alois.schloegl@gmail.com>
|
||||
% Copyright (C) 2014-2017 Dynare Team
|
||||
%
|
||||
% This is part of the NaN-toolbox. For more details see
|
||||
% 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
|
||||
% the Free Software Foundation; either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% This program 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.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with this program; If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
|
||||
% check size of arguments
|
||||
if all(size(x)==1)
|
||||
x = repmat(x,size(n));
|
||||
elseif all(size(n)==1)
|
||||
n = repmat(n,size(x));
|
||||
elseif all(size(x)==size(n))
|
||||
% OK, do nothing
|
||||
else
|
||||
error('size of input arguments must be equal or scalar')
|
||||
end
|
||||
|
||||
% allocate memory
|
||||
p = zeros(size(x));
|
||||
p((x==Inf) & (n>0)) = 1;
|
||||
|
||||
% workaround for invalid arguments in BETAINC
|
||||
ix = isnan(x) | ~(n>0);
|
||||
p(ix)= NaN;
|
||||
|
||||
ix = (x > -Inf) & (x < Inf) & (n > 0);
|
||||
p(ix) = betainc (n(ix) ./ (n(ix) + x(ix).^2), n(ix)/2, 1/2) / 2;
|
||||
|
||||
ix = find(x>0);
|
||||
p(ix) = 1 - p(ix);
|
||||
|
||||
% shape output
|
||||
p = reshape(p,size(x));
|
||||
|
||||
%!assert(tcdf(NaN,4),NaN)
|
||||
|
|
@ -41,7 +41,7 @@ case ${host_os} in
|
|||
esac
|
||||
|
||||
OCTAVE_VERSION=$($MKOCTFILE -v 2>&1 | sed 's/mkoctfile, version //')
|
||||
AX_COMPARE_VERSION([$OCTAVE_VERSION], [lt], [4.2], [AC_MSG_ERROR([Your Octave is too old, please upgrade to version 4.2 at least (or disable Octave support with --disable-octave).])])
|
||||
AX_COMPARE_VERSION([$OCTAVE_VERSION], [lt], [4.4], [AC_MSG_ERROR([Your Octave is too old, please upgrade to version 4.4 at least (or disable Octave support with --disable-octave).])])
|
||||
|
||||
AC_PROG_F77([gfortran g77 f77])
|
||||
AC_PROG_CC
|
||||
|
|
|
|||
Loading…
Reference in New Issue