1 | // $Id: Polynomial.cc 728 2007-01-04 16:07:16Z peter $ |
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2 | |
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3 | /* |
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4 | Copyright (C) The authors contributing to this file. |
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5 | |
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6 | This file is part of the yat library, http://lev.thep.lu.se/trac/yat |
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7 | |
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8 | The yat library is free software; you can redistribute it and/or |
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9 | modify it under the terms of the GNU General Public License as |
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10 | published by the Free Software Foundation; either version 2 of the |
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11 | License, or (at your option) any later version. |
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12 | |
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13 | The yat library is distributed in the hope that it will be useful, |
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14 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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15 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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16 | General Public License for more details. |
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17 | |
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18 | You should have received a copy of the GNU General Public License |
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19 | along with this program; if not, write to the Free Software |
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20 | Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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21 | 02111-1307, USA. |
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22 | */ |
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23 | |
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24 | #include "Polynomial.h" |
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25 | #include "yat/utility/matrix.h" |
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26 | #include "yat/utility/vector.h" |
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27 | |
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28 | namespace theplu { |
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29 | namespace yat { |
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30 | namespace regression { |
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31 | |
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32 | Polynomial::Polynomial(size_t power) |
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33 | : OneDimensional(), power_(power) |
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34 | { |
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35 | } |
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36 | |
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37 | |
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38 | Polynomial::~Polynomial(void) |
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39 | { |
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40 | } |
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41 | |
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42 | |
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43 | double Polynomial::chisq(void) const |
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44 | { |
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45 | return md_.chisq(); |
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46 | } |
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47 | |
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48 | |
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49 | const utility::matrix& Polynomial::covariance(void) const |
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50 | { |
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51 | return md_.covariance(); |
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52 | } |
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53 | |
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54 | |
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55 | void Polynomial::fit(const utility::vector& x, const utility::vector& y) |
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56 | { |
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57 | utility::matrix X=utility::matrix(x.size(),power_+1,1); |
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58 | for (size_t i=0; i<X.rows(); ++i) |
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59 | for (u_int j=1; j<X.columns(); j++) |
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60 | X(i,j)=X(i,j-1)*x(i); |
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61 | md_.fit(X,y); |
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62 | } |
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63 | |
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64 | |
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65 | const utility::vector& Polynomial::fit_parameters(void) const |
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66 | { |
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67 | return md_.fit_parameters(); |
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68 | } |
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69 | |
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70 | |
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71 | double Polynomial::predict(const double x) const |
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72 | { |
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73 | utility::vector vec(power_+1,1); |
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74 | for (size_t i=1; i<=power_; ++i) |
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75 | vec(i) = vec(i-1)*x; |
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76 | return md_.predict(vec); |
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77 | } |
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78 | |
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79 | |
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80 | double Polynomial::s2(void) const |
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81 | { |
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82 | return chisq()/(ap_.n()-power_-1); |
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83 | } |
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84 | |
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85 | |
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86 | double Polynomial::standard_error2(const double x) const |
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87 | { |
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88 | utility::vector vec(power_+1,1); |
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89 | for (size_t i=1; i<=power_; ++i) |
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90 | vec(i) = vec(i-1)*x; |
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91 | return md_.standard_error2(vec); |
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92 | } |
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93 | |
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94 | }}} // of namespaces regression, yat, and theplu |
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