annotate m-toolbox/classes/@ao/kstest.m @ 36:5eb86f6881ef database-connection-manager

Remove commented-out code
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % KSTEST perform KS test on input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: Kolmogorov - Smirnov test is typically used to assess if a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % sample comes from a specific distribution or if two data samples came
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % from the same distribution. The test statistics is d_K = max|S(x) - K(x)|
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % where S(x) and K(x) are cumulative distribution functions of the two
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % inputs respectively.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % In the case of the test on a single data series:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % - null hypothesis is that the data are a realizations of a random variable
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % which is distributed according to the given probability distribution
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % In the case of the test on two data series:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % - null hypothesis is that the two data series are realizations of the same random variable
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % CALL: b = kstest(a1, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % b = kstest(a1, a2, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % b = kstest(a1, a2, a3, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % INPUT: ai: are real valued AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % OUTPUT: b: are cdata AOs containing the results of the test:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % true if the null hypothesis is rejected
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % at the given significance level.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % false if the null hypothesis is not rejected
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % at the given significance level.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % The procinfo of b contain further information as:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 % - KSstatistic, the value of d_K = max|S(x) - K(x)|.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % - criticalValue, it is the value of the test statistics
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % corresponding to the significance level. CRITICAL VALUE
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % is depending on K, where K is the data length of Y1 if Y2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % is a theoretical distribution, otherwise if Y1 and Y2 are
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 % two data samples K = n1*n2/(n1 + n2) where n1 and n2 are
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % data length of Y1 and Y2 respectively. In the case of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % comparison of a data series with a theoretical
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % distribution and the data series is composed of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 % correlated elements. K can be adjusted with a shape
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 % parameter in order to recover test fairness. In such a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 % case the test is performed for K' = Phi * K. If
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % KSstatistic > criticalValue the null hypothesis is
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 % rejected.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 % - pValue, it is the probability value associated to the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 % test statistic.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'kstest')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 % VERSION: $Id: kstest.m,v 1.5 2011/07/14 07:09:06 mauro Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 function varargout = kstest(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 error('### KSTEST cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 % Collect input histories
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 inhists = [as.hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 if isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 model = 'empirical';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 model = lower(find(pl, 'TESTDISTRIBUTION'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 if isempty(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 model = 'empirical';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 pl.pset('TESTDISTRIBUTION', model);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 pl = parse(pl, getDefaultPlist(model));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 % get parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 alpha = find(pl, 'ALPHA');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 if isa(alpha, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 alpha = alpha.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 shapeparam = find(pl, 'SHAPEPARAM');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 if isa(shapeparam, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 shapeparam = shapeparam.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 criticalvalue = find(pl, 'CRITICALVALUE');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 if isa(criticalvalue, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 criticalvalue = criticalvalue.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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102 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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103
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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104 % switch among test type
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105 switch lower(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 case 'normal'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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107 mmean = find(pl, 'MEAN');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108 if isa(mmean, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 mmean = mmean.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 sstd = find(pl, 'STD');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 if isa(sstd, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 sstd = sstd.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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115 distparams = [mmean, sstd];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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116 dist = 'normdist';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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117 case 'chi2'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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118 ddof = find(pl, 'DOF');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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119 if isa(ddof, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 ddof = ddof.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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121 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122 distparams = [ddof];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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123 dist = 'chi2dist';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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124 case 'f'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125 dof1 = find(pl, 'DOF1');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126 if isa(dof1, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127 dof1 = dof1.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 dof2 = find(pl, 'DOF2');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 if isa(dof2, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 dof2 = dof2.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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132 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 distparams = [dof1, dof2];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 dist = 'fdist';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 case 'gamma'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 shp = find(pl, 'SHAPE');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 if isa(shp, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 shp = shp.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 scl = find(pl, 'SCALE');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 if isa(scl, 'ao')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 scl = scl.y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 distparams = [shp, scl];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 dist = 'gammadist';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 distparams = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 % run test
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 switch lower(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 case 'empirical'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 y1 = as(1).y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 bs = ao.initObjectWithSize(1, numel(as)-1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 % run over input aos
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 for ii = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 y2 = as(ii+1).y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 if size(y1, 1) ~= size(y2, 1)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 % reshape
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 y2 = y2.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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162 [H, KSstatistic, criticalValue, pValue] =...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163 utils.math.kstest(y1, y2, alpha, distparams, shapeparam, criticalvalue);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 bs(ii) = ao(H);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 bs(ii).setName(sprintf('KStest(%s,%s)', as(1).name, as(ii+1).name));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 plproc = plist(...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 'KSstatistic', KSstatistic,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 'criticalValue', criticalValue,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 'pValue', pValue);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 bs(ii).setProcinfo(plproc);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 bs(ii).addHistory(getInfo('None'), pl, [ao_invars(1) ao_invars(ii+1)], [inhists(1) inhists(ii+1)]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 otherwise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 bs = ao.initObjectWithSize(1, numel(as));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 % run over input aos
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 for ii = 1:numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 [H, KSstatistic, criticalValue, pValue] =...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180 utils.math.kstest(as(ii).y, dist, alpha, distparams, shapeparam, criticalvalue);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 bs(ii) = ao(H);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 bs(ii).setName(sprintf('KStest(%s,%s)', as(ii).name,model));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 plproc = plist(...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 'KSstatistic',KSstatistic,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 'criticalValue',criticalValue,...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 'pValue',pValue);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 bs(ii).setProcinfo(plproc);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 bs(ii).addHistory(getInfo('None'), pl, ao_invars(ii), inhists(ii));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194 % Set output
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 varargout = utils.helper.setoutputs(nargout, bs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 % Get Info Object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 function ii = getInfo(varargin)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 elseif nargin == 1 && ~isempty(varargin{1}) && ischar(varargin{1})
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 sets{1} = varargin{1};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 pl = getDefaultPlist(sets{1});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 sets = SETS();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 % get plists
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 pl(size(sets)) = plist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 for kk = 1:numel(sets)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 pl(kk) = getDefaultPlist(sets{kk});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 % Build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: kstest.m,v 1.5 2011/07/14 07:09:06 mauro Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 % Defintion of Sets
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 function out = SETS()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 out = {...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 'empirical', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 'normal', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 'chi2', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 'f', ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 'gamma' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 };
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 function plout = getDefaultPlist(set)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 persistent lastset;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 if ~exist('pl', 'var') || isempty(pl) || ~strcmp(lastset, set)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 pl = buildplist(set);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 lastset = set;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 function plo = buildplist(set)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 plo = plist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 p = param({'TESTDISTRIBUTION', ['test data are compared with the given '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 'test distribution. Available choices are:<ol>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255 '<li>EMPIRICAL test all the input objects (starting from the second) against the first object.</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 '<li>NORMAL test all the input objects against the Normal distribution, '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257 'with mean specified by the ''MEAN'' parameter, and sigma specified by the ''STD'' parameter</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 '<li>CHI2 test all the input objects against the Chi square distribution, ' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 'with degrees of freedom specified by the ''DOF'' parameter</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 '<li>F test all the input objects against the F distribution, '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 'with first degree of freedom specified by the ''DOF1'' parameter, and '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262 'second degree of freedom specified by the ''DOF2'' parameter</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 '<li>GAMMA test all the input objects against the Gamma distribution, '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 'with shape parameter (k) specified by the ''SHAPE'' parameter, '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 'and scale parameter (theta) specified by the ''SCALE'' parameter</li></ol>']}, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266 {1, {'EMPIRICAL', 'NORMAL', 'CHI2', 'F', 'GAMMA'}, paramValue.SINGLE});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 p = param({'ALPHA', ['ALPHA is the desired significance level. It represents '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270 'the probability of rejecting the null hypothesis when it is true.'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271 'Rejecting the null hypothesis, H0, when it is true is called a Type I '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272 'Error. Therefore, if the null hypothesis is true , the level of the test, '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273 'is the probability of a type I error.']}, paramValue.DOUBLE_VALUE(0.05));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
276 p = param({'SHAPEPARAM', ['In the case of comparison of a data series with a '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
277 'theoretical distribution and the data series is composed of correlated '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
278 'elements. K can be adjusted with a shape parameter in order to recover '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
279 'test fairness [3]. In such a case the test is performed for K* = Phi * K.<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
280 'Phi is the corresponding Shape parameter. The shape parameter depends on '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
281 'the correlations and on the significance value. It does not depend on '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
282 'data length.']}, paramValue.DOUBLE_VALUE(1));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
283 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
284
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
285 p = param({'CRITICALVALUE', ['In case the critical value for the test is available from '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
286 'external calculations, e.g. Monte Carlo simulation, the vale can be input '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
287 'as a parameter.']}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
288 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
289
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
290 switch lower(set)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
291 case 'empirical'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
292 % do nothing
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
293 case 'normal'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
294 p = param({'MEAN', ['The mean of the normal distribution']}, paramValue.DOUBLE_VALUE(0));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
295 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
296 p = param({'STD', ['The standard deviation of the normal distribution']}, paramValue.DOUBLE_VALUE(1));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
297 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
298 case 'chi2'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
299 p = param({'DOF', ['Degrees of freedom of the Chi square distribution']}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
300 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
301 case 'f'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
302 p = param({'DOF1', ['First degree of freedom of the F distribution']}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
303 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
304 p = param({'DOF2', ['Second degree of freedom of the F distribution']}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
305 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
306 case 'gamma'
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
307 p = param({'SHAPE', ['Shape parameter (k) of the Gamma distribution']}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
308 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
309 p = param({'SCALE', ['Scale parameter (theta) of the Gamma distribution']}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
310 plo.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
311 otherwise
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
312 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
313
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
314
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
315
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
316
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
317 end