| 1 | |
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| 2 | /*! |
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| 3 | \file |
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| 4 | \brief Robust |
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| 5 | \author Vasek Smidl |
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| 6 | |
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| 7 | */ |
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| 8 | |
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| 9 | #include "robustlib.h" |
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| 10 | #include <vector> |
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| 11 | #include <iostream> |
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| 12 | #include <fstream> |
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| 13 | |
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| 14 | using namespace itpp; |
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| 15 | //using namespace bdm; |
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| 16 | |
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| 17 | const int emlig_size = 2; |
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| 18 | |
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| 19 | |
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| 20 | int main ( int argc, char* argv[] ) { |
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| 21 | |
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| 22 | /* |
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| 23 | // EXPERIMENT: 100 AR model generated time series of length of 30 from y_t=0.95*y_(t-1)+0.05*y_(t-2)+0.2*e_t, |
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| 24 | // where e_t is normally, student(4) and cauchy distributed are tested using robust AR model, to obtain the |
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| 25 | // variance of location parameter estimators and compare it to the classical setup. |
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| 26 | vector<vector<vector<string>>> string_lists; |
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| 27 | string_lists.push_back(vector<vector<string>>()); |
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| 28 | string_lists.push_back(vector<vector<string>>()); |
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| 29 | string_lists.push_back(vector<vector<string>>()); |
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| 30 | |
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| 31 | char* file_strings[3] = {"c:\\ar_normal.txt", "c:\\ar_student.txt", "c:\\ar_cauchy.txt"}; |
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| 32 | |
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| 33 | |
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| 34 | for(int i = 0;i<3;i++) |
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| 35 | { |
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| 36 | ifstream myfile(file_strings[i]); |
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| 37 | if (myfile.is_open()) |
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| 38 | { |
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| 39 | while ( myfile.good() ) |
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| 40 | { |
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| 41 | string line; |
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| 42 | getline(myfile,line); |
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| 43 | |
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| 44 | vector<string> parsed_line; |
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| 45 | while(line.find(',') != string::npos) |
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| 46 | { |
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| 47 | int loc = line.find(','); |
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| 48 | parsed_line.push_back(line.substr(0,loc)); |
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| 49 | line.erase(0,loc+1); |
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| 50 | } |
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| 51 | |
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| 52 | string_lists[i].push_back(parsed_line); |
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| 53 | } |
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| 54 | myfile.close(); |
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| 55 | } |
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| 56 | } |
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| 57 | |
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| 58 | for(int j = 0;j<string_lists.size();j++) |
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| 59 | { |
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| 60 | |
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| 61 | for(int i = 0;i<string_lists[j].size()-1;i++) |
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| 62 | { |
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| 63 | vector<vec> conditions; |
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| 64 | //emlig* emliga = new emlig(2); |
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| 65 | RARX* my_rarx = new RARX(2,30); |
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| 66 | |
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| 67 | for(int k = 1;k<string_lists[j][i].size();k++) |
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| 68 | { |
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| 69 | vec condition; |
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| 70 | //condition.ins(0,1); |
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| 71 | condition.ins(0,string_lists[j][i][k]); |
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| 72 | conditions.push_back(condition); |
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| 73 | |
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| 74 | //cout << "orig:" << condition << endl; |
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| 75 | |
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| 76 | if(conditions.size()>1) |
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| 77 | { |
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| 78 | conditions[k-2].ins(0,string_lists[j][i][k]); |
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| 79 | |
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| 80 | } |
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| 81 | |
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| 82 | if(conditions.size()>2) |
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| 83 | { |
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| 84 | conditions[k-3].ins(0,string_lists[j][i][k]); |
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| 85 | |
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| 86 | //cout << "modi:" << conditions[k-3] << endl; |
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| 87 | |
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| 88 | my_rarx->bayes(conditions[k-3]); |
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| 89 | |
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| 90 | |
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| 91 | //if(k>5) |
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| 92 | //{ |
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| 93 | // cout << "MaxLik coords:" << emliga->minimal_vertex->get_coordinates() << endl; |
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| 94 | //} |
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| 95 | |
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| 96 | } |
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| 97 | |
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| 98 | } |
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| 99 | |
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| 100 | //emliga->step_me(0); |
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| 101 | /* |
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| 102 | ofstream myfile; |
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| 103 | myfile.open("c:\\robust_ar1.txt",ios::app); |
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| 104 | myfile << my_rarx->minimal_vertex->get_coordinates()[0] << ";"; |
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| 105 | myfile.close(); |
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| 106 | |
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| 107 | myfile.open("c:\\robust_ar2.txt",ios::app); |
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| 108 | myfile << emliga->minimal_vertex->get_coordinates()[1] << ";"; |
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| 109 | myfile.close(); |
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| 110 | |
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| 111 | |
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| 112 | cout << "MaxLik coords:" << emliga->minimal_vertex->get_coordinates() << endl; |
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| 113 | cout << "Step: " << i << endl; |
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| 114 | } |
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| 115 | |
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| 116 | cout << "One experiment finished." << endl; |
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| 117 | |
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| 118 | ofstream myfile; |
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| 119 | myfile.open("c:\\robust_ar1.txt",ios::app); |
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| 120 | myfile << endl; |
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| 121 | myfile.close(); |
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| 122 | |
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| 123 | myfile.open("c:\\robust_ar2.txt",ios::app); |
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| 124 | myfile << endl; |
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| 125 | myfile.close(); |
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| 126 | }*/ |
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| 127 | |
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| 128 | |
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| 129 | // EXPERIMENT: A moving window estimation and prediction of RARX is tested on data generated from |
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| 130 | // y_t=0.95*y_(t-1)+0.05*y_(t-2)+0.2*e_t, where e_t is normally, student(4) and cauchy distributed. It |
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| 131 | // can be compared to the classical setup. |
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| 132 | |
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| 133 | |
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| 134 | vector<vector<string>> strings; |
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| 135 | |
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| 136 | char* file_strings[3] = {"c:\\ar_student_single.txt", "c:\\ar_cauchy_single.txt","c:\\ar_normal_single.txt"}; |
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| 137 | |
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| 138 | for(int i = 0;i<3;i++) |
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| 139 | { |
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| 140 | ifstream myfile(file_strings[i]); |
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| 141 | if (myfile.is_open()) |
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| 142 | { |
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| 143 | string line; |
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| 144 | getline(myfile,line); |
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| 145 | |
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| 146 | vector<string> parsed_line; |
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| 147 | while(line.find(',') != string::npos) |
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| 148 | { |
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| 149 | int loc = line.find(','); |
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| 150 | parsed_line.push_back(line.substr(0,loc)); |
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| 151 | line.erase(0,loc+1); |
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| 152 | } |
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| 153 | |
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| 154 | strings.push_back(parsed_line); |
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| 155 | |
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| 156 | myfile.close(); |
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| 157 | } |
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| 158 | } |
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| 159 | |
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| 160 | for(int j = 0;j<strings.size();j++) |
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| 161 | { |
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| 162 | vector<vec> conditions; |
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| 163 | //emlig* emliga = new emlig(2); |
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| 164 | RARX* my_rarx = new RARX(2,30); |
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| 165 | |
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| 166 | for(int k = 1;k<170;k++) |
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| 167 | { |
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| 168 | vec condition; |
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| 169 | //condition.ins(0,1); |
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| 170 | condition.ins(0,strings[j][k]); |
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| 171 | conditions.push_back(condition); |
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| 172 | |
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| 173 | //cout << "orig:" << condition << endl; |
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| 174 | |
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| 175 | if(conditions.size()>1) |
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| 176 | { |
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| 177 | conditions[k-2].ins(0,strings[j][k]); |
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| 178 | |
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| 179 | } |
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| 180 | |
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| 181 | if(conditions.size()>2) |
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| 182 | { |
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| 183 | conditions[k-3].ins(0,strings[j][k]); |
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| 184 | |
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| 185 | // cout << "modi:" << conditions[k-3] << endl; |
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| 186 | |
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| 187 | my_rarx->bayes(conditions[k-3]); |
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| 188 | |
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| 189 | |
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| 190 | |
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| 191 | if(k>5) |
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| 192 | { |
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| 193 | cout << "MaxLik coords:" << my_rarx->posterior->minimal_vertex->get_coordinates() << endl; |
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| 194 | |
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| 195 | ofstream myfile; |
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| 196 | char fstring[80]; |
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| 197 | strcpy(fstring,file_strings[j]); |
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| 198 | strcat(fstring,"_res.txt"); |
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| 199 | |
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| 200 | myfile.open(fstring,ios::app); |
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| 201 | myfile << my_rarx->posterior->minimal_vertex->get_coordinates()[0]; |
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| 202 | if(k!=strings[j].size()-1) |
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| 203 | { |
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| 204 | myfile << ","; |
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| 205 | } |
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| 206 | else |
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| 207 | { |
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| 208 | myfile << endl; |
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| 209 | } |
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| 210 | myfile.close(); |
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| 211 | } |
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| 212 | } |
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| 213 | |
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| 214 | //emliga->step_me(0); |
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| 215 | /* |
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| 216 | ofstream myfile; |
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| 217 | myfile.open("c:\\robust_ar1.txt",ios::app); |
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| 218 | myfile << my_rarx->minimal_vertex->get_coordinates()[0] << ";"; |
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| 219 | myfile.close(); |
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| 220 | |
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| 221 | myfile.open("c:\\robust_ar2.txt",ios::app); |
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| 222 | myfile << emliga->minimal_vertex->get_coordinates()[1] << ";"; |
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| 223 | myfile.close(); |
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| 224 | |
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| 225 | |
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| 226 | cout << "MaxLik coords:" << emliga->minimal_vertex->get_coordinates() << endl; |
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| 227 | cout << "Step: " << i << endl;*/ |
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| 228 | } |
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| 229 | } |
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| 230 | |
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| 231 | /* |
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| 232 | cout << "One experiment finished." << endl; |
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| 233 | |
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| 234 | ofstream myfile; |
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| 235 | myfile.open("c:\\robust_ar1.txt",ios::app); |
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| 236 | myfile << endl; |
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| 237 | myfile.close(); |
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| 238 | |
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| 239 | myfile.open("c:\\robust_ar2.txt",ios::app); |
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| 240 | myfile << endl; |
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| 241 | myfile.close();*/ |
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| 242 | |
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| 243 | |
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| 244 | //emlig* emlig1 = new emlig(emlig_size); |
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| 245 | |
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| 246 | //emlig1->step_me(0); |
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| 247 | //emlig* emlig2 = new emlig(emlig_size); |
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| 248 | |
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| 249 | /* |
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| 250 | emlig1->set_correction_factors(4); |
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| 251 | |
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| 252 | for(int j = 0;j<emlig1->correction_factors.size();j++) |
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| 253 | { |
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| 254 | for(set<my_ivec>::iterator vec_ref = emlig1->correction_factors[j].begin();vec_ref!=emlig1->correction_factors[j].end();vec_ref++) |
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| 255 | { |
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| 256 | cout << j << " "; |
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| 257 | |
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| 258 | for(int i=0;i<(*vec_ref).size();i++) |
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| 259 | { |
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| 260 | cout << (*vec_ref)[i]; |
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| 261 | } |
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| 262 | |
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| 263 | cout << endl; |
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| 264 | } |
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| 265 | }*/ |
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| 266 | |
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| 267 | /* |
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| 268 | vec condition5 = "1.0 1.0 1.01";//"-0.3 1.7 1.5"; |
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| 269 | |
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| 270 | emlig1->add_condition(condition5); |
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| 271 | //emlig1->step_me(0); |
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| 272 | |
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| 273 | |
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| 274 | vec condition1a = "-1.0 1.02 0.5"; |
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| 275 | //vec condition1b = "1.0 1.0 1.01"; |
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| 276 | emlig1->add_condition(condition1a); |
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| 277 | //emlig2->add_condition(condition1b); |
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| 278 | |
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| 279 | vec condition2a = "-0.3 1.7 1.5"; |
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| 280 | //vec condition2b = "-1.0 1.0 1.0"; |
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| 281 | emlig1->add_condition(condition2a); |
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| 282 | //emlig2->add_condition(condition2b); |
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| 283 | |
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| 284 | vec condition3a = "0.5 -1.01 1.0"; |
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| 285 | //vec condition3b = "0.5 -1.01 1.0"; |
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| 286 | |
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| 287 | emlig1->add_condition(condition3a); |
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| 288 | //emlig2->add_condition(condition3b); |
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| 289 | |
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| 290 | vec condition4a = "-0.5 -1.0 1.0"; |
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| 291 | //vec condition4b = "-0.5 -1.0 1.0"; |
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| 292 | |
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| 293 | emlig1->add_condition(condition4a); |
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| 294 | //cout << "************************************************" << endl; |
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| 295 | //emlig2->add_condition(condition4b); |
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| 296 | //cout << "************************************************" << endl; |
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| 297 | |
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| 298 | //cout << emlig1->minimal_vertex->get_coordinates(); |
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| 299 | |
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| 300 | //emlig1->remove_condition(condition3a); |
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| 301 | //emlig1->step_me(0); |
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| 302 | //emlig1->remove_condition(condition2a); |
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| 303 | //emlig1->remove_condition(condition1a); |
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| 304 | //emlig1->remove_condition(condition5); |
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| 305 | |
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| 306 | |
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| 307 | //emlig1->step_me(0); |
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| 308 | //emlig2->step_me(0); |
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| 309 | |
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| 310 | |
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| 311 | // DA SE POUZIT PRO VYPIS DO SOUBORU |
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| 312 | // emlig1->step_me(0); |
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| 313 | |
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| 314 | //emlig1->remove_condition(condition1); |
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| 315 | |
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| 316 | |
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| 317 | |
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| 318 | |
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| 319 | |
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| 320 | /* |
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| 321 | for(int i = 0;i<100;i++) |
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| 322 | { |
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| 323 | cout << endl << "Step:" << i << endl; |
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| 324 | |
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| 325 | double condition[emlig_size+1]; |
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| 326 | |
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| 327 | for(int k = 0;k<=emlig_size;k++) |
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| 328 | { |
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| 329 | condition[k] = (rand()-RAND_MAX/2)/1000.0; |
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| 330 | } |
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| 331 | |
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| 332 | |
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| 333 | vec* condition_vec = new vec(condition,emlig_size+1); |
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| 334 | emlig1->add_condition(*condition_vec); |
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| 335 | |
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| 336 | /* |
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| 337 | for(polyhedron* toprow_ref = emlig1->statistic.rows[emlig_size]; toprow_ref != emlig1->statistic.end_poly; toprow_ref = toprow_ref->next_poly) |
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| 338 | { |
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| 339 | cout << ((toprow*)toprow_ref)->probability << endl; |
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| 340 | } |
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| 341 | */ |
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| 342 | /* |
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| 343 | cout << emlig1->statistic_rowsize(emlig_size) << endl << endl; |
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| 344 | |
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| 345 | /* |
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| 346 | if(i-emlig1->number_of_parameters >= 0) |
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| 347 | { |
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| 348 | pause(30); |
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| 349 | } |
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| 350 | */ |
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| 351 | |
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| 352 | // emlig1->step_me(i); |
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| 353 | |
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| 354 | /* |
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| 355 | vector<int> sizevector; |
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| 356 | for(int s = 0;s<=emlig1->number_of_parameters;s++) |
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| 357 | { |
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| 358 | sizevector.push_back(emlig1->statistic_rowsize(s)); |
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| 359 | } |
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| 360 | */ |
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| 361 | //} |
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| 362 | |
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| 363 | |
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| 364 | |
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| 365 | |
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| 366 | /* |
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| 367 | emlig1->step_me(1); |
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| 368 | |
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| 369 | vec condition = "2.0 0.0 1.0"; |
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| 370 | |
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| 371 | emlig1->add_condition(condition); |
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| 372 | |
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| 373 | vector<int> sizevector; |
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| 374 | for(int s = 0;s<=emlig1->number_of_parameters;s++) |
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| 375 | { |
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| 376 | sizevector.push_back(emlig1->statistic_rowsize(s)); |
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| 377 | } |
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| 378 | |
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| 379 | emlig1->step_me(2); |
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| 380 | |
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| 381 | condition = "2.0 1.0 0.0"; |
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| 382 | |
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| 383 | emlig1->add_condition(condition); |
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| 384 | |
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| 385 | sizevector.clear(); |
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| 386 | for(int s = 0;s<=emlig1->number_of_parameters;s++) |
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| 387 | { |
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| 388 | sizevector.push_back(emlig1->statistic_rowsize(s)); |
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| 389 | } |
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| 390 | */ |
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| 391 | |
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| 392 | return 0; |
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| 393 | } |
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| 394 | |
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| 395 | |
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