source: trunk/yat/statistics/tTest.h @ 1275

Last change on this file since 1275 was 1275, checked in by Jari Häkkinen, 13 years ago

Updating copyright statements.

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1#ifndef _theplu_yat_statistics_ttest_
2#define _theplu_yat_statistics_ttest_
3
4// $Id: tTest.h 1275 2008-04-11 06:10:12Z jari $
5
6/*
7  Copyright (C) 2004, 2005 Peter Johansson
8  Copyright (C) 2006 Jari Häkkinen, Peter Johansson, Markus Ringnér
9  Copyright (C) 2007 Jari Häkkinen, Peter Johansson
10  Copyright (C) 2008 Peter Johansson
11
12  This file is part of the yat library, http://trac.thep.lu.se/yat
13
14  The yat library is free software; you can redistribute it and/or
15  modify it under the terms of the GNU General Public License as
16  published by the Free Software Foundation; either version 2 of the
17  License, or (at your option) any later version.
18
19  The yat library is distributed in the hope that it will be useful,
20  but WITHOUT ANY WARRANTY; without even the implied warranty of
21  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
22  General Public License for more details.
23
24  You should have received a copy of the GNU General Public License
25  along with this program; if not, write to the Free Software
26  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
27  02111-1307, USA.
28*/
29
30#include "AveragerWeighted.h"
31
32#include <gsl/gsl_cdf.h>
33
34namespace theplu {
35namespace yat {
36namespace statistics { 
37
38  ///
39  /// @brief Class for Student's t-test.
40  ///   
41  /// See <a href="http://en.wikipedia.org/wiki/Student's_t-test">
42  /// http://en.wikipedia.org/wiki/Student's_t-test</a> for more
43  /// details on the t-test.
44  ///
45  class tTest
46  {
47 
48  public:
49    ///
50    /// @brief Default Constructor.
51    ///
52    tTest(void);
53
54   
55    /**
56       Adding a data value to tTest.
57    */
58    void add(double value, bool target, double weight=1.0);
59
60    /**
61       Calculates the t-score, i.e. the ratio between difference in
62       mean and standard deviation of this difference. The t-score is
63       calculated as
64       \f$ t = \frac{ m_x - m_y }{
65       s\sqrt{\frac{1}{n_x}+\frac{1}{n_y}}} \f$ where \f$ m \f$ is the
66       weighted mean, n is the weighted version of number of data
67       points \f$ \frac{\left(\sum w_i\right)^2}{\sum w_i^2} \f$, and
68       \f$ s^2 \f$ is an estimation of the variance \f$ s^2 = \frac{
69       \sum_i w_i(x_i-m_x)^2 + \sum_i w_i(y_i-m_y)^2 }{ n_x + n_y - 2
70       } \f$
71
72       \see AveragerWeighted
73
74       If all weights are equal to unity this boils down to
75       \f$ t = \frac{ m_x - m_y }
76       {s\sqrt{\frac{1}{n_x}+\frac{1}{n_y}}} \f$ where \f$ m \f$ is
77       the mean, \f$ n \f$ is the number of data points and \f$ s^2 =
78       \frac{ \sum_i (x_i-m_x)^2 + \sum_i (y_i-m_y)^2 }{ n_x + n_y - 2
79       } \f$
80
81       \see Averager
82       
83       \return t-score.
84    */
85    double score(void); 
86
87    ///
88    /// Calculates the p-value, i.e. the probability of observing a
89    /// t-score equally or larger if the null hypothesis is true. If P
90    /// is near zero, this casts doubt on this hypothesis. The null
91    /// hypothesis is that the means of the two distributions are
92    /// equal. Assumtions for this test is that the two distributions
93    /// are normal distributions with equal variance. The latter
94    /// assumtion is dropped in Welch's t-test.
95    ///
96    /// @return the two-sided p-value
97    ///
98    double p_value() const;
99
100    ///
101    /// @return One-sided P-value
102    ///
103    double p_value_one_sided(void) const;
104
105  private:
106
107    double dof_;
108    bool updated_;
109    double t_;
110    AveragerWeighted pos_;
111    AveragerWeighted neg_;
112
113  };
114
115}}} // of namespace statistics, yat, and theplu
116
117#endif
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