Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationThu, 05 Dec 2013 13:35:02 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/05/t13862687165z3wjaxqtaer874.htm/, Retrieved Thu, 28 Mar 2024 18:06:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231208, Retrieved Thu, 28 Mar 2024 18:06:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Recursive Partitioning (Regression Trees)] [] [2013-12-05 18:35:02] [cb53f031a0ffd0579ef217f9e7726ef4] [Current]
Feedback Forum

Post a new message
Dataseries X:
119.992 157.302 74.997 0.00784 0.00007 0.0037 0.00554 0.04374 0.426 0.02971 1
122.4 148.65 113.819 0.00968 0.00008 0.00465 0.00696 0.06134 0.626 0.04368 1
116.682 131.111 111.555 0.0105 0.00009 0.00544 0.00781 0.05233 0.482 0.0359 1
116.676 137.871 111.366 0.00997 0.00009 0.00502 0.00698 0.05492 0.517 0.03772 1
116.014 141.781 110.655 0.01284 0.00011 0.00655 0.00908 0.06425 0.584 0.04465 1
120.552 131.162 113.787 0.00968 0.00008 0.00463 0.0075 0.04701 0.456 0.03243 1
120.267 137.244 114.82 0.00333 0.00003 0.00155 0.00202 0.01608 0.14 0.01351 1
107.332 113.84 104.315 0.0029 0.00003 0.00144 0.00182 0.01567 0.134 0.01256 1
95.73 132.068 91.754 0.00551 0.00006 0.00293 0.00332 0.02093 0.191 0.01717 1
95.056 120.103 91.226 0.00532 0.00006 0.00268 0.00332 0.02838 0.255 0.02444 1
88.333 112.24 84.072 0.00505 0.00006 0.00254 0.0033 0.02143 0.197 0.01892 1
91.904 115.871 86.292 0.0054 0.00006 0.00281 0.00336 0.02752 0.249 0.02214 1
136.926 159.866 131.276 0.00293 0.00002 0.00118 0.00153 0.01259 0.112 0.0114 1
139.173 179.139 76.556 0.0039 0.00003 0.00165 0.00208 0.01642 0.154 0.01797 1
152.845 163.305 75.836 0.00294 0.00002 0.00121 0.00149 0.01828 0.158 0.01246 1
142.167 217.455 83.159 0.00369 0.00003 0.00157 0.00203 0.01503 0.126 0.01359 1
144.188 349.259 82.764 0.00544 0.00004 0.00211 0.00292 0.02047 0.192 0.02074 1
168.778 232.181 75.603 0.00718 0.00004 0.00284 0.00387 0.03327 0.348 0.0343 1
153.046 175.829 68.623 0.00742 0.00005 0.00364 0.00432 0.05517 0.542 0.05767 1
156.405 189.398 142.822 0.00768 0.00005 0.00372 0.00399 0.03995 0.348 0.0431 1
153.848 165.738 65.782 0.0084 0.00005 0.00428 0.0045 0.0381 0.328 0.04055 1
153.88 172.86 78.128 0.0048 0.00003 0.00232 0.00267 0.04137 0.37 0.04525 1
167.93 193.221 79.068 0.00442 0.00003 0.0022 0.00247 0.04351 0.377 0.04246 1
173.917 192.735 86.18 0.00476 0.00003 0.00221 0.00258 0.04192 0.364 0.03772 1
163.656 200.841 76.779 0.00742 0.00005 0.0038 0.0039 0.01659 0.164 0.01497 1
104.4 206.002 77.968 0.00633 0.00006 0.00316 0.00375 0.03767 0.381 0.0378 1
171.041 208.313 75.501 0.00455 0.00003 0.0025 0.00234 0.01966 0.186 0.01872 1
146.845 208.701 81.737 0.00496 0.00003 0.0025 0.00275 0.01919 0.198 0.01826 1
155.358 227.383 80.055 0.0031 0.00002 0.00159 0.00176 0.01718 0.161 0.01661 1
162.568 198.346 77.63 0.00502 0.00003 0.0028 0.00253 0.01791 0.168 0.01799 1
197.076 206.896 192.055 0.00289 0.00001 0.00166 0.00168 0.01098 0.097 0.00802 0
199.228 209.512 192.091 0.00241 0.00001 0.00134 0.00138 0.01015 0.089 0.00762 0
198.383 215.203 193.104 0.00212 0.00001 0.00113 0.00135 0.01263 0.111 0.00951 0
202.266 211.604 197.079 0.0018 0.000009 0.00093 0.00107 0.00954 0.085 0.00719 0
203.184 211.526 196.16 0.00178 0.000009 0.00094 0.00106 0.00958 0.085 0.00726 0
201.464 210.565 195.708 0.00198 0.00001 0.00105 0.00115 0.01194 0.107 0.00957 0
177.876 192.921 168.013 0.00411 0.00002 0.00233 0.00241 0.02126 0.189 0.01612 1
176.17 185.604 163.564 0.00369 0.00002 0.00205 0.00218 0.01851 0.168 0.01491 1
180.198 201.249 175.456 0.00284 0.00002 0.00153 0.00166 0.01444 0.131 0.0119 1
187.733 202.324 173.015 0.00316 0.00002 0.00168 0.00182 0.01663 0.151 0.01366 1
186.163 197.724 177.584 0.00298 0.00002 0.00165 0.00175 0.01495 0.135 0.01233 1
184.055 196.537 166.977 0.00258 0.00001 0.00134 0.00147 0.01463 0.132 0.01234 1
237.226 247.326 225.227 0.00298 0.00001 0.00169 0.00182 0.01752 0.164 0.01133 0
241.404 248.834 232.483 0.00281 0.00001 0.00157 0.00173 0.0176 0.154 0.01251 0
243.439 250.912 232.435 0.0021 0.000009 0.00109 0.00137 0.01419 0.126 0.01033 0
242.852 255.034 227.911 0.00225 0.000009 0.00117 0.00139 0.01494 0.134 0.01014 0
245.51 262.09 231.848 0.00235 0.00001 0.00127 0.00148 0.01608 0.141 0.01149 0
252.455 261.487 182.786 0.00185 0.000007 0.00092 0.00113 0.01152 0.103 0.0086 0
122.188 128.611 115.765 0.00524 0.00004 0.00169 0.00203 0.01613 0.143 0.01433 0
122.964 130.049 114.676 0.00428 0.00003 0.00124 0.00155 0.01681 0.154 0.014 0
124.445 135.069 117.495 0.00431 0.00003 0.00141 0.00167 0.02184 0.197 0.01685 0
126.344 134.231 112.773 0.00448 0.00004 0.00131 0.00169 0.02033 0.185 0.01614 0
128.001 138.052 122.08 0.00436 0.00003 0.00137 0.00166 0.02297 0.21 0.01677 0
129.336 139.867 118.604 0.0049 0.00004 0.00165 0.00183 0.02498 0.228 0.01947 0
108.807 134.656 102.874 0.00761 0.00007 0.00349 0.00486 0.02719 0.255 0.02067 1
109.86 126.358 104.437 0.00874 0.00008 0.00398 0.00539 0.03209 0.307 0.02454 1
110.417 131.067 103.37 0.00784 0.00007 0.00352 0.00514 0.03715 0.334 0.02802 1
117.274 129.916 110.402 0.00752 0.00006 0.00299 0.00469 0.02293 0.221 0.01948 1
116.879 131.897 108.153 0.00788 0.00007 0.00334 0.00493 0.02645 0.265 0.02137 1
114.847 271.314 104.68 0.00867 0.00008 0.00373 0.0052 0.03225 0.35 0.02519 1
209.144 237.494 109.379 0.00282 0.00001 0.00147 0.00152 0.01861 0.17 0.01382 0
223.365 238.987 98.664 0.00264 0.00001 0.00154 0.00151 0.01906 0.165 0.0134 0
222.236 231.345 205.495 0.00266 0.00001 0.00152 0.00144 0.01643 0.145 0.012 0
228.832 234.619 223.634 0.00296 0.00001 0.00175 0.00155 0.01644 0.145 0.01179 0
229.401 252.221 221.156 0.00205 0.000009 0.00114 0.00113 0.01457 0.129 0.01016 0
228.969 239.541 113.201 0.00238 0.00001 0.00136 0.0014 0.01745 0.154 0.01234 0
140.341 159.774 67.021 0.00817 0.00006 0.0043 0.0044 0.03198 0.313 0.02428 1
136.969 166.607 66.004 0.00923 0.00007 0.00507 0.00463 0.03111 0.308 0.02603 1
143.533 162.215 65.809 0.01101 0.00008 0.00647 0.00467 0.05384 0.478 0.03392 1
148.09 162.824 67.343 0.00762 0.00005 0.00467 0.00354 0.05428 0.497 0.03635 1
142.729 162.408 65.476 0.00831 0.00006 0.00469 0.00419 0.03485 0.365 0.02949 1
136.358 176.595 65.75 0.00971 0.00007 0.00534 0.00478 0.04978 0.483 0.03736 1
120.08 139.71 111.208 0.00405 0.00003 0.0018 0.0022 0.01706 0.152 0.01345 1
112.014 588.518 107.024 0.00533 0.00005 0.00268 0.00329 0.02448 0.226 0.01956 1
110.793 128.101 107.316 0.00494 0.00004 0.0026 0.00283 0.02442 0.216 0.01831 1
110.707 122.611 105.007 0.00516 0.00005 0.00277 0.00289 0.02215 0.206 0.01715 1
112.876 148.826 106.981 0.005 0.00004 0.0027 0.00289 0.03999 0.35 0.02704 1
110.568 125.394 106.821 0.00462 0.00004 0.00226 0.0028 0.02199 0.197 0.01636 1
95.385 102.145 90.264 0.00608 0.00006 0.00331 0.00332 0.03202 0.263 0.02455 1
100.77 115.697 85.545 0.01038 0.0001 0.00622 0.00576 0.03121 0.361 0.02139 1
96.106 108.664 84.51 0.00694 0.00007 0.00389 0.00415 0.04024 0.364 0.02876 1
95.605 107.715 87.549 0.00702 0.00007 0.00428 0.00371 0.03156 0.296 0.0219 1
100.96 110.019 95.628 0.00606 0.00006 0.00351 0.00348 0.02427 0.216 0.01751 1
98.804 102.305 87.804 0.00432 0.00004 0.00247 0.00258 0.02223 0.202 0.01552 1
176.858 205.56 75.344 0.00747 0.00004 0.00418 0.0042 0.04795 0.435 0.0351 1
180.978 200.125 155.495 0.00406 0.00002 0.0022 0.00244 0.03852 0.331 0.02877 1
178.222 202.45 141.047 0.00321 0.00002 0.00163 0.00194 0.03759 0.327 0.02784 1
176.281 227.381 125.61 0.0052 0.00003 0.00287 0.00312 0.06511 0.58 0.04683 1
173.898 211.35 74.677 0.00448 0.00003 0.00237 0.00254 0.06727 0.65 0.04802 1
179.711 225.93 144.878 0.00709 0.00004 0.00391 0.00419 0.04313 0.442 0.03455 1
166.605 206.008 78.032 0.00742 0.00004 0.00387 0.00453 0.0664 0.634 0.05114 1
151.955 163.335 147.226 0.00419 0.00003 0.00224 0.00227 0.07959 0.772 0.0569 1
148.272 164.989 142.299 0.00459 0.00003 0.0025 0.00256 0.0419 0.383 0.03051 1
152.125 161.469 76.596 0.00382 0.00003 0.00191 0.00226 0.05925 0.637 0.04398 1
157.821 172.975 68.401 0.00358 0.00002 0.00196 0.00196 0.03716 0.307 0.02764 1
157.447 163.267 149.605 0.00369 0.00002 0.00201 0.00197 0.03272 0.283 0.02571 1
159.116 168.913 144.811 0.00342 0.00002 0.00178 0.00184 0.03381 0.307 0.02809 1
125.036 143.946 116.187 0.0128 0.0001 0.00743 0.00623 0.03886 0.342 0.03088 1
125.791 140.557 96.206 0.01378 0.00011 0.00826 0.00655 0.04689 0.422 0.03908 1
126.512 141.756 99.77 0.01936 0.00015 0.01159 0.0099 0.06734 0.659 0.05783 1
125.641 141.068 116.346 0.03316 0.00026 0.02144 0.01522 0.09178 0.891 0.06196 1
128.451 150.449 75.632 0.01551 0.00012 0.00905 0.00909 0.0617 0.584 0.05174 1
139.224 586.567 66.157 0.03011 0.00022 0.01854 0.01628 0.09419 0.93 0.06023 1
150.258 154.609 75.349 0.00248 0.00002 0.00105 0.00136 0.01131 0.107 0.01009 1
154.003 160.267 128.621 0.00183 0.00001 0.00076 0.001 0.0103 0.094 0.00871 1
149.689 160.368 133.608 0.00257 0.00002 0.00116 0.00134 0.01346 0.126 0.01059 1
155.078 163.736 144.148 0.00168 0.00001 0.00068 0.00092 0.01064 0.097 0.00928 1
151.884 157.765 133.751 0.00258 0.00002 0.00115 0.00122 0.0145 0.137 0.01267 1
151.989 157.339 132.857 0.00174 0.00001 0.00075 0.00096 0.01024 0.093 0.00993 1
193.03 208.9 80.297 0.00766 0.00004 0.0045 0.00389 0.03044 0.275 0.02084 1
200.714 223.982 89.686 0.00621 0.00003 0.00371 0.00337 0.02286 0.207 0.01852 1
208.519 220.315 199.02 0.00609 0.00003 0.00368 0.00339 0.01761 0.155 0.01307 1
204.664 221.3 189.621 0.00841 0.00004 0.00502 0.00485 0.02378 0.21 0.01767 1
210.141 232.706 185.258 0.00534 0.00003 0.00321 0.0028 0.0168 0.149 0.01301 1
206.327 226.355 92.02 0.00495 0.00002 0.00302 0.00246 0.02105 0.209 0.01604 1
151.872 492.892 69.085 0.00856 0.00006 0.00404 0.00385 0.01843 0.235 0.01271 1
158.219 442.557 71.948 0.00476 0.00003 0.00214 0.00207 0.01458 0.148 0.01312 1
170.756 450.247 79.032 0.00555 0.00003 0.00244 0.00261 0.01725 0.175 0.01652 1
178.285 442.824 82.063 0.00462 0.00003 0.00157 0.00194 0.01279 0.129 0.01151 1
217.116 233.481 93.978 0.00404 0.00002 0.00127 0.00128 0.01299 0.124 0.01075 1
128.94 479.697 88.251 0.00581 0.00005 0.00241 0.00314 0.02008 0.221 0.01734 1
176.824 215.293 83.961 0.0046 0.00003 0.00209 0.00221 0.01169 0.117 0.01104 1
138.19 203.522 83.34 0.00704 0.00005 0.00406 0.00398 0.04479 0.441 0.0322 1
182.018 197.173 79.187 0.00842 0.00005 0.00506 0.00449 0.02503 0.231 0.01931 1
156.239 195.107 79.82 0.00694 0.00004 0.00403 0.00395 0.02343 0.224 0.0172 1
145.174 198.109 80.637 0.00733 0.00005 0.00414 0.00422 0.02362 0.233 0.01944 1
138.145 197.238 81.114 0.00544 0.00004 0.00294 0.00327 0.02791 0.246 0.02259 1
166.888 198.966 79.512 0.00638 0.00004 0.00368 0.00351 0.02857 0.257 0.02301 1
119.031 127.533 109.216 0.0044 0.00004 0.00214 0.00192 0.01033 0.098 0.00811 1
120.078 126.632 105.667 0.0027 0.00002 0.00116 0.00135 0.01022 0.09 0.00903 1
120.289 128.143 100.209 0.00492 0.00004 0.00269 0.00238 0.01412 0.125 0.01194 1
120.256 125.306 104.773 0.00407 0.00003 0.00224 0.00205 0.01516 0.138 0.0131 1
119.056 125.213 86.795 0.00346 0.00003 0.00169 0.0017 0.01201 0.106 0.00915 1
118.747 123.723 109.836 0.00331 0.00003 0.00168 0.00171 0.01043 0.099 0.00903 1
106.516 112.777 93.105 0.00589 0.00006 0.00291 0.00319 0.04932 0.441 0.03651 1
110.453 127.611 105.554 0.00494 0.00004 0.00244 0.00315 0.04128 0.379 0.03316 1
113.4 133.344 107.816 0.00451 0.00004 0.00219 0.00283 0.04879 0.431 0.0437 1
113.166 130.27 100.673 0.00502 0.00004 0.00257 0.00312 0.05279 0.476 0.04134 1
112.239 126.609 104.095 0.00472 0.00004 0.00238 0.0029 0.05643 0.517 0.04451 1
116.15 131.731 109.815 0.00381 0.00003 0.00181 0.00232 0.03026 0.267 0.0277 1
170.368 268.796 79.543 0.00571 0.00003 0.00232 0.00269 0.03273 0.281 0.02824 1
208.083 253.792 91.802 0.00757 0.00004 0.00428 0.00428 0.06725 0.571 0.04464 1
198.458 219.29 148.691 0.00376 0.00002 0.00182 0.00215 0.03527 0.297 0.0253 1
202.805 231.508 86.232 0.0037 0.00002 0.00189 0.00211 0.01997 0.18 0.01506 1
202.544 241.35 164.168 0.00254 0.00001 0.001 0.00133 0.02662 0.228 0.02006 1
223.361 263.872 87.638 0.00352 0.00002 0.00169 0.00188 0.02536 0.225 0.01909 1
169.774 191.759 151.451 0.01568 0.00009 0.00863 0.00946 0.08143 0.821 0.08808 1
183.52 216.814 161.34 0.01466 0.00008 0.00849 0.00819 0.0605 0.618 0.06359 1
188.62 216.302 165.982 0.01719 0.00009 0.00996 0.01027 0.07118 0.722 0.06824 1
202.632 565.74 177.258 0.01627 0.00008 0.00919 0.00963 0.0717 0.833 0.0646 1
186.695 211.961 149.442 0.01872 0.0001 0.01075 0.01154 0.0583 0.784 0.06259 1
192.818 224.429 168.793 0.03107 0.00016 0.018 0.01958 0.11908 1.302 0.13778 1
198.116 233.099 174.478 0.02714 0.00014 0.01568 0.01699 0.08684 1.018 0.08318 1
121.345 139.644 98.25 0.00684 0.00006 0.00388 0.00332 0.02534 0.241 0.02056 1
119.1 128.442 88.833 0.00692 0.00006 0.00393 0.003 0.02682 0.236 0.02018 1
117.87 127.349 95.654 0.00647 0.00005 0.00356 0.003 0.03087 0.276 0.02402 1
122.336 142.369 94.794 0.00727 0.00006 0.00415 0.00339 0.02293 0.223 0.01771 1
117.963 134.209 100.757 0.01813 0.00015 0.01117 0.00718 0.04912 0.438 0.02916 1
126.144 154.284 97.543 0.00975 0.00008 0.00593 0.00454 0.02852 0.266 0.02157 1
127.93 138.752 112.173 0.00605 0.00005 0.00321 0.00318 0.03235 0.339 0.03105 1
114.238 124.393 77.022 0.00581 0.00005 0.00299 0.00316 0.04009 0.406 0.04114 1
115.322 135.738 107.802 0.00619 0.00005 0.00352 0.00329 0.03273 0.325 0.02931 1
114.554 126.778 91.121 0.00651 0.00006 0.00366 0.0034 0.03658 0.369 0.03091 1
112.15 131.669 97.527 0.00519 0.00005 0.00291 0.00284 0.01756 0.155 0.01363 1
102.273 142.83 85.902 0.00907 0.00009 0.00493 0.00461 0.02814 0.272 0.02073 1
236.2 244.663 102.137 0.00277 0.00001 0.00154 0.00153 0.02448 0.217 0.01621 0
237.323 243.709 229.256 0.00303 0.00001 0.00173 0.00159 0.01242 0.116 0.00882 0
260.105 264.919 237.303 0.00339 0.00001 0.00205 0.00186 0.0203 0.197 0.01367 0
197.569 217.627 90.794 0.00803 0.00004 0.0049 0.00448 0.02177 0.189 0.01439 0
240.301 245.135 219.783 0.00517 0.00002 0.00316 0.00283 0.02018 0.212 0.01344 0
244.99 272.21 239.17 0.00451 0.00002 0.00279 0.00237 0.01897 0.181 0.01255 0
112.547 133.374 105.715 0.00355 0.00003 0.00166 0.0019 0.01358 0.129 0.0114 0
110.739 113.597 100.139 0.00356 0.00003 0.0017 0.002 0.01484 0.133 0.01285 0
113.715 116.443 96.913 0.00349 0.00003 0.00171 0.00203 0.01472 0.133 0.01148 0
117.004 144.466 99.923 0.00353 0.00003 0.00176 0.00218 0.01657 0.145 0.01318 0
115.38 123.109 108.634 0.00332 0.00003 0.0016 0.00199 0.01503 0.137 0.01133 0
116.388 129.038 108.97 0.00346 0.00003 0.00169 0.00213 0.01725 0.155 0.01331 0
151.737 190.204 129.859 0.00314 0.00002 0.00135 0.00162 0.01469 0.132 0.0123 1
148.79 158.359 138.99 0.00309 0.00002 0.00152 0.00186 0.01574 0.142 0.01309 1
148.143 155.982 135.041 0.00392 0.00003 0.00204 0.00231 0.0145 0.131 0.01263 1
150.44 163.441 144.736 0.00396 0.00003 0.00206 0.00233 0.02551 0.237 0.02148 1
148.462 161.078 141.998 0.00397 0.00003 0.00202 0.00235 0.01831 0.163 0.01559 1
149.818 163.417 144.786 0.00336 0.00002 0.00174 0.00198 0.02145 0.198 0.01666 1
117.226 123.925 106.656 0.00417 0.00004 0.00186 0.0027 0.01909 0.171 0.01949 0
116.848 217.552 99.503 0.00531 0.00005 0.0026 0.00346 0.01795 0.163 0.01756 0
116.286 177.291 96.983 0.00314 0.00003 0.00134 0.00192 0.01564 0.136 0.01691 0
116.556 592.03 86.228 0.00496 0.00004 0.00254 0.00263 0.0166 0.154 0.01491 0
116.342 581.289 94.246 0.00267 0.00002 0.00115 0.00148 0.013 0.117 0.01144 0
114.563 119.167 86.647 0.00327 0.00003 0.00146 0.00184 0.01185 0.106 0.01095 0
201.774 262.707 78.228 0.00694 0.00003 0.00412 0.00396 0.02574 0.255 0.01758 0
174.188 230.978 94.261 0.00459 0.00003 0.00263 0.00259 0.04087 0.405 0.02745 0
209.516 253.017 89.488 0.00564 0.00003 0.00331 0.00292 0.02751 0.263 0.01879 0
174.688 240.005 74.287 0.0136 0.00008 0.00624 0.00564 0.02308 0.256 0.01667 0
198.764 396.961 74.904 0.0074 0.00004 0.0037 0.0039 0.02296 0.241 0.01588 0
214.289 260.277 77.973 0.00567 0.00003 0.00295 0.00317 0.01884 0.19 0.01373 0
  




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 16 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231208&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231208&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231208&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Goodness of Fit
Correlation0.8022
R-squared0.6435
RMSE0.2572

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.8022 \tabularnewline
R-squared & 0.6435 \tabularnewline
RMSE & 0.2572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231208&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.8022[/C][/ROW]
[ROW][C]R-squared[/C][C]0.6435[/C][/ROW]
[ROW][C]RMSE[/C][C]0.2572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231208&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231208&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Goodness of Fit
Correlation0.8022
R-squared0.6435
RMSE0.2572







Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
110.98750.0125
210.98750.0125
310.98750.0125
410.98750.0125
510.98750.0125
610.98750.0125
710.2727272727272730.727272727272727
810.2727272727272730.727272727272727
910.8823529411764710.117647058823529
1010.98750.0125
1110.8823529411764710.117647058823529
1210.98750.0125
13110
14110
15110
16110
1710.8571428571428570.142857142857143
1810.98750.0125
1910.98750.0125
2010.98750.0125
2110.98750.0125
2210.98750.0125
2310.98750.0125
2410.98750.0125
2510.8571428571428570.142857142857143
2610.98750.0125
27110
28110
29110
30110
31000
32000
33000
34000
35000
36000
37110
38110
39110
40110
41110
42110
43000
44000
45000
46000
47000
48000
4900.272727272727273-0.272727272727273
5000.272727272727273-0.272727272727273
5100.272727272727273-0.272727272727273
5200.272727272727273-0.272727272727273
5300.272727272727273-0.272727272727273
5400.272727272727273-0.272727272727273
5510.98750.0125
5610.98750.0125
5710.98750.0125
5810.8823529411764710.117647058823529
5910.98750.0125
6010.98750.0125
61000
62000
63000
64000
65000
66000
6710.98750.0125
6810.98750.0125
6910.98750.0125
7010.98750.0125
7110.98750.0125
7210.98750.0125
7310.2727272727272730.727272727272727
7410.8823529411764710.117647058823529
7510.8823529411764710.117647058823529
7610.8823529411764710.117647058823529
7710.98750.0125
7810.8823529411764710.117647058823529
7910.98750.0125
8010.98750.0125
8110.98750.0125
8210.98750.0125
8310.8823529411764710.117647058823529
8410.8823529411764710.117647058823529
8510.98750.0125
8610.98750.0125
8710.98750.0125
8810.98750.0125
8910.98750.0125
9010.98750.0125
9110.98750.0125
9210.98750.0125
9310.98750.0125
9410.98750.0125
9510.98750.0125
9610.98750.0125
9710.98750.0125
9810.98750.0125
9910.98750.0125
10010.98750.0125
10110.98750.0125
10210.98750.0125
10310.98750.0125
104110
105110
106110
107110
108110
109110
11010.98750.0125
11110.6428571428571430.357142857142857
11210.5714285714285710.428571428571429
11310.6428571428571430.357142857142857
11410.5714285714285710.428571428571429
11510.6428571428571430.357142857142857
11610.8571428571428570.142857142857143
117110
11810.8571428571428570.142857142857143
119110
12010.5714285714285710.428571428571429
12110.8823529411764710.117647058823529
122110
12310.98750.0125
12410.98750.0125
12510.8571428571428570.142857142857143
12610.8571428571428570.142857142857143
12710.98750.0125
12810.98750.0125
12910.8823529411764710.117647058823529
13010.2727272727272730.727272727272727
13110.8823529411764710.117647058823529
13210.8823529411764710.117647058823529
13310.2727272727272730.727272727272727
13410.2727272727272730.727272727272727
13510.98750.0125
13610.98750.0125
13710.98750.0125
13810.98750.0125
13910.98750.0125
14010.98750.0125
14110.98750.0125
14210.6428571428571430.357142857142857
14310.6428571428571430.357142857142857
14410.5714285714285710.428571428571429
14510.6428571428571430.357142857142857
14610.6428571428571430.357142857142857
14710.98750.0125
14810.98750.0125
14910.98750.0125
15010.6428571428571430.357142857142857
15110.98750.0125
15210.98750.0125
15310.6428571428571430.357142857142857
15410.98750.0125
15510.98750.0125
15610.98750.0125
15710.8823529411764710.117647058823529
15810.98750.0125
15910.98750.0125
16010.98750.0125
16110.98750.0125
16210.98750.0125
16310.98750.0125
16410.8823529411764710.117647058823529
16510.98750.0125
16600.642857142857143-0.642857142857143
167000
168000
16900.642857142857143-0.642857142857143
17000.571428571428571-0.571428571428571
17100.571428571428571-0.571428571428571
17200.272727272727273-0.272727272727273
17300.272727272727273-0.272727272727273
17400.272727272727273-0.272727272727273
17500.272727272727273-0.272727272727273
17600.272727272727273-0.272727272727273
17700.272727272727273-0.272727272727273
178110
179110
180110
18110.98750.0125
182110
183110
18400.272727272727273-0.272727272727273
18500.882352941176471-0.882352941176471
18600.272727272727273-0.272727272727273
18700.882352941176471-0.882352941176471
18800.272727272727273-0.272727272727273
18900.272727272727273-0.272727272727273
19000.642857142857143-0.642857142857143
19100.9875-0.9875
19200.642857142857143-0.642857142857143
19300.857142857142857-0.857142857142857
19400.642857142857143-0.642857142857143
19500.571428571428571-0.571428571428571

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 1 & 0.9875 & 0.0125 \tabularnewline
2 & 1 & 0.9875 & 0.0125 \tabularnewline
3 & 1 & 0.9875 & 0.0125 \tabularnewline
4 & 1 & 0.9875 & 0.0125 \tabularnewline
5 & 1 & 0.9875 & 0.0125 \tabularnewline
6 & 1 & 0.9875 & 0.0125 \tabularnewline
7 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
8 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
9 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
10 & 1 & 0.9875 & 0.0125 \tabularnewline
11 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
12 & 1 & 0.9875 & 0.0125 \tabularnewline
13 & 1 & 1 & 0 \tabularnewline
14 & 1 & 1 & 0 \tabularnewline
15 & 1 & 1 & 0 \tabularnewline
16 & 1 & 1 & 0 \tabularnewline
17 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
18 & 1 & 0.9875 & 0.0125 \tabularnewline
19 & 1 & 0.9875 & 0.0125 \tabularnewline
20 & 1 & 0.9875 & 0.0125 \tabularnewline
21 & 1 & 0.9875 & 0.0125 \tabularnewline
22 & 1 & 0.9875 & 0.0125 \tabularnewline
23 & 1 & 0.9875 & 0.0125 \tabularnewline
24 & 1 & 0.9875 & 0.0125 \tabularnewline
25 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
26 & 1 & 0.9875 & 0.0125 \tabularnewline
27 & 1 & 1 & 0 \tabularnewline
28 & 1 & 1 & 0 \tabularnewline
29 & 1 & 1 & 0 \tabularnewline
30 & 1 & 1 & 0 \tabularnewline
31 & 0 & 0 & 0 \tabularnewline
32 & 0 & 0 & 0 \tabularnewline
33 & 0 & 0 & 0 \tabularnewline
34 & 0 & 0 & 0 \tabularnewline
35 & 0 & 0 & 0 \tabularnewline
36 & 0 & 0 & 0 \tabularnewline
37 & 1 & 1 & 0 \tabularnewline
38 & 1 & 1 & 0 \tabularnewline
39 & 1 & 1 & 0 \tabularnewline
40 & 1 & 1 & 0 \tabularnewline
41 & 1 & 1 & 0 \tabularnewline
42 & 1 & 1 & 0 \tabularnewline
43 & 0 & 0 & 0 \tabularnewline
44 & 0 & 0 & 0 \tabularnewline
45 & 0 & 0 & 0 \tabularnewline
46 & 0 & 0 & 0 \tabularnewline
47 & 0 & 0 & 0 \tabularnewline
48 & 0 & 0 & 0 \tabularnewline
49 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
50 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
51 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
52 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
53 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
54 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
55 & 1 & 0.9875 & 0.0125 \tabularnewline
56 & 1 & 0.9875 & 0.0125 \tabularnewline
57 & 1 & 0.9875 & 0.0125 \tabularnewline
58 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
59 & 1 & 0.9875 & 0.0125 \tabularnewline
60 & 1 & 0.9875 & 0.0125 \tabularnewline
61 & 0 & 0 & 0 \tabularnewline
62 & 0 & 0 & 0 \tabularnewline
63 & 0 & 0 & 0 \tabularnewline
64 & 0 & 0 & 0 \tabularnewline
65 & 0 & 0 & 0 \tabularnewline
66 & 0 & 0 & 0 \tabularnewline
67 & 1 & 0.9875 & 0.0125 \tabularnewline
68 & 1 & 0.9875 & 0.0125 \tabularnewline
69 & 1 & 0.9875 & 0.0125 \tabularnewline
70 & 1 & 0.9875 & 0.0125 \tabularnewline
71 & 1 & 0.9875 & 0.0125 \tabularnewline
72 & 1 & 0.9875 & 0.0125 \tabularnewline
73 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
74 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
75 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
76 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
77 & 1 & 0.9875 & 0.0125 \tabularnewline
78 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
79 & 1 & 0.9875 & 0.0125 \tabularnewline
80 & 1 & 0.9875 & 0.0125 \tabularnewline
81 & 1 & 0.9875 & 0.0125 \tabularnewline
82 & 1 & 0.9875 & 0.0125 \tabularnewline
83 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
84 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
85 & 1 & 0.9875 & 0.0125 \tabularnewline
86 & 1 & 0.9875 & 0.0125 \tabularnewline
87 & 1 & 0.9875 & 0.0125 \tabularnewline
88 & 1 & 0.9875 & 0.0125 \tabularnewline
89 & 1 & 0.9875 & 0.0125 \tabularnewline
90 & 1 & 0.9875 & 0.0125 \tabularnewline
91 & 1 & 0.9875 & 0.0125 \tabularnewline
92 & 1 & 0.9875 & 0.0125 \tabularnewline
93 & 1 & 0.9875 & 0.0125 \tabularnewline
94 & 1 & 0.9875 & 0.0125 \tabularnewline
95 & 1 & 0.9875 & 0.0125 \tabularnewline
96 & 1 & 0.9875 & 0.0125 \tabularnewline
97 & 1 & 0.9875 & 0.0125 \tabularnewline
98 & 1 & 0.9875 & 0.0125 \tabularnewline
99 & 1 & 0.9875 & 0.0125 \tabularnewline
100 & 1 & 0.9875 & 0.0125 \tabularnewline
101 & 1 & 0.9875 & 0.0125 \tabularnewline
102 & 1 & 0.9875 & 0.0125 \tabularnewline
103 & 1 & 0.9875 & 0.0125 \tabularnewline
104 & 1 & 1 & 0 \tabularnewline
105 & 1 & 1 & 0 \tabularnewline
106 & 1 & 1 & 0 \tabularnewline
107 & 1 & 1 & 0 \tabularnewline
108 & 1 & 1 & 0 \tabularnewline
109 & 1 & 1 & 0 \tabularnewline
110 & 1 & 0.9875 & 0.0125 \tabularnewline
111 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
112 & 1 & 0.571428571428571 & 0.428571428571429 \tabularnewline
113 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
114 & 1 & 0.571428571428571 & 0.428571428571429 \tabularnewline
115 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
116 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
117 & 1 & 1 & 0 \tabularnewline
118 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
119 & 1 & 1 & 0 \tabularnewline
120 & 1 & 0.571428571428571 & 0.428571428571429 \tabularnewline
121 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
122 & 1 & 1 & 0 \tabularnewline
123 & 1 & 0.9875 & 0.0125 \tabularnewline
124 & 1 & 0.9875 & 0.0125 \tabularnewline
125 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
126 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
127 & 1 & 0.9875 & 0.0125 \tabularnewline
128 & 1 & 0.9875 & 0.0125 \tabularnewline
129 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
130 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
131 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
132 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
133 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
134 & 1 & 0.272727272727273 & 0.727272727272727 \tabularnewline
135 & 1 & 0.9875 & 0.0125 \tabularnewline
136 & 1 & 0.9875 & 0.0125 \tabularnewline
137 & 1 & 0.9875 & 0.0125 \tabularnewline
138 & 1 & 0.9875 & 0.0125 \tabularnewline
139 & 1 & 0.9875 & 0.0125 \tabularnewline
140 & 1 & 0.9875 & 0.0125 \tabularnewline
141 & 1 & 0.9875 & 0.0125 \tabularnewline
142 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
143 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
144 & 1 & 0.571428571428571 & 0.428571428571429 \tabularnewline
145 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
146 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
147 & 1 & 0.9875 & 0.0125 \tabularnewline
148 & 1 & 0.9875 & 0.0125 \tabularnewline
149 & 1 & 0.9875 & 0.0125 \tabularnewline
150 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
151 & 1 & 0.9875 & 0.0125 \tabularnewline
152 & 1 & 0.9875 & 0.0125 \tabularnewline
153 & 1 & 0.642857142857143 & 0.357142857142857 \tabularnewline
154 & 1 & 0.9875 & 0.0125 \tabularnewline
155 & 1 & 0.9875 & 0.0125 \tabularnewline
156 & 1 & 0.9875 & 0.0125 \tabularnewline
157 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
158 & 1 & 0.9875 & 0.0125 \tabularnewline
159 & 1 & 0.9875 & 0.0125 \tabularnewline
160 & 1 & 0.9875 & 0.0125 \tabularnewline
161 & 1 & 0.9875 & 0.0125 \tabularnewline
162 & 1 & 0.9875 & 0.0125 \tabularnewline
163 & 1 & 0.9875 & 0.0125 \tabularnewline
164 & 1 & 0.882352941176471 & 0.117647058823529 \tabularnewline
165 & 1 & 0.9875 & 0.0125 \tabularnewline
166 & 0 & 0.642857142857143 & -0.642857142857143 \tabularnewline
167 & 0 & 0 & 0 \tabularnewline
168 & 0 & 0 & 0 \tabularnewline
169 & 0 & 0.642857142857143 & -0.642857142857143 \tabularnewline
170 & 0 & 0.571428571428571 & -0.571428571428571 \tabularnewline
171 & 0 & 0.571428571428571 & -0.571428571428571 \tabularnewline
172 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
173 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
174 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
175 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
176 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
177 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
178 & 1 & 1 & 0 \tabularnewline
179 & 1 & 1 & 0 \tabularnewline
180 & 1 & 1 & 0 \tabularnewline
181 & 1 & 0.9875 & 0.0125 \tabularnewline
182 & 1 & 1 & 0 \tabularnewline
183 & 1 & 1 & 0 \tabularnewline
184 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
185 & 0 & 0.882352941176471 & -0.882352941176471 \tabularnewline
186 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
187 & 0 & 0.882352941176471 & -0.882352941176471 \tabularnewline
188 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
189 & 0 & 0.272727272727273 & -0.272727272727273 \tabularnewline
190 & 0 & 0.642857142857143 & -0.642857142857143 \tabularnewline
191 & 0 & 0.9875 & -0.9875 \tabularnewline
192 & 0 & 0.642857142857143 & -0.642857142857143 \tabularnewline
193 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
194 & 0 & 0.642857142857143 & -0.642857142857143 \tabularnewline
195 & 0 & 0.571428571428571 & -0.571428571428571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231208&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.571428571428571[/C][C]0.428571428571429[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.571428571428571[/C][C]0.428571428571429[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.571428571428571[/C][C]0.428571428571429[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.272727272727273[/C][C]0.727272727272727[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.571428571428571[/C][C]0.428571428571429[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.642857142857143[/C][C]0.357142857142857[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.882352941176471[/C][C]0.117647058823529[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.642857142857143[/C][C]-0.642857142857143[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.642857142857143[/C][C]-0.642857142857143[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.571428571428571[/C][C]-0.571428571428571[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.571428571428571[/C][C]-0.571428571428571[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.9875[/C][C]0.0125[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]1[/C][C]0[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.882352941176471[/C][C]-0.882352941176471[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.882352941176471[/C][C]-0.882352941176471[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.272727272727273[/C][C]-0.272727272727273[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.642857142857143[/C][C]-0.642857142857143[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.9875[/C][C]-0.9875[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.642857142857143[/C][C]-0.642857142857143[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.642857142857143[/C][C]-0.642857142857143[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.571428571428571[/C][C]-0.571428571428571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231208&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231208&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
110.98750.0125
210.98750.0125
310.98750.0125
410.98750.0125
510.98750.0125
610.98750.0125
710.2727272727272730.727272727272727
810.2727272727272730.727272727272727
910.8823529411764710.117647058823529
1010.98750.0125
1110.8823529411764710.117647058823529
1210.98750.0125
13110
14110
15110
16110
1710.8571428571428570.142857142857143
1810.98750.0125
1910.98750.0125
2010.98750.0125
2110.98750.0125
2210.98750.0125
2310.98750.0125
2410.98750.0125
2510.8571428571428570.142857142857143
2610.98750.0125
27110
28110
29110
30110
31000
32000
33000
34000
35000
36000
37110
38110
39110
40110
41110
42110
43000
44000
45000
46000
47000
48000
4900.272727272727273-0.272727272727273
5000.272727272727273-0.272727272727273
5100.272727272727273-0.272727272727273
5200.272727272727273-0.272727272727273
5300.272727272727273-0.272727272727273
5400.272727272727273-0.272727272727273
5510.98750.0125
5610.98750.0125
5710.98750.0125
5810.8823529411764710.117647058823529
5910.98750.0125
6010.98750.0125
61000
62000
63000
64000
65000
66000
6710.98750.0125
6810.98750.0125
6910.98750.0125
7010.98750.0125
7110.98750.0125
7210.98750.0125
7310.2727272727272730.727272727272727
7410.8823529411764710.117647058823529
7510.8823529411764710.117647058823529
7610.8823529411764710.117647058823529
7710.98750.0125
7810.8823529411764710.117647058823529
7910.98750.0125
8010.98750.0125
8110.98750.0125
8210.98750.0125
8310.8823529411764710.117647058823529
8410.8823529411764710.117647058823529
8510.98750.0125
8610.98750.0125
8710.98750.0125
8810.98750.0125
8910.98750.0125
9010.98750.0125
9110.98750.0125
9210.98750.0125
9310.98750.0125
9410.98750.0125
9510.98750.0125
9610.98750.0125
9710.98750.0125
9810.98750.0125
9910.98750.0125
10010.98750.0125
10110.98750.0125
10210.98750.0125
10310.98750.0125
104110
105110
106110
107110
108110
109110
11010.98750.0125
11110.6428571428571430.357142857142857
11210.5714285714285710.428571428571429
11310.6428571428571430.357142857142857
11410.5714285714285710.428571428571429
11510.6428571428571430.357142857142857
11610.8571428571428570.142857142857143
117110
11810.8571428571428570.142857142857143
119110
12010.5714285714285710.428571428571429
12110.8823529411764710.117647058823529
122110
12310.98750.0125
12410.98750.0125
12510.8571428571428570.142857142857143
12610.8571428571428570.142857142857143
12710.98750.0125
12810.98750.0125
12910.8823529411764710.117647058823529
13010.2727272727272730.727272727272727
13110.8823529411764710.117647058823529
13210.8823529411764710.117647058823529
13310.2727272727272730.727272727272727
13410.2727272727272730.727272727272727
13510.98750.0125
13610.98750.0125
13710.98750.0125
13810.98750.0125
13910.98750.0125
14010.98750.0125
14110.98750.0125
14210.6428571428571430.357142857142857
14310.6428571428571430.357142857142857
14410.5714285714285710.428571428571429
14510.6428571428571430.357142857142857
14610.6428571428571430.357142857142857
14710.98750.0125
14810.98750.0125
14910.98750.0125
15010.6428571428571430.357142857142857
15110.98750.0125
15210.98750.0125
15310.6428571428571430.357142857142857
15410.98750.0125
15510.98750.0125
15610.98750.0125
15710.8823529411764710.117647058823529
15810.98750.0125
15910.98750.0125
16010.98750.0125
16110.98750.0125
16210.98750.0125
16310.98750.0125
16410.8823529411764710.117647058823529
16510.98750.0125
16600.642857142857143-0.642857142857143
167000
168000
16900.642857142857143-0.642857142857143
17000.571428571428571-0.571428571428571
17100.571428571428571-0.571428571428571
17200.272727272727273-0.272727272727273
17300.272727272727273-0.272727272727273
17400.272727272727273-0.272727272727273
17500.272727272727273-0.272727272727273
17600.272727272727273-0.272727272727273
17700.272727272727273-0.272727272727273
178110
179110
180110
18110.98750.0125
182110
183110
18400.272727272727273-0.272727272727273
18500.882352941176471-0.882352941176471
18600.272727272727273-0.272727272727273
18700.882352941176471-0.882352941176471
18800.272727272727273-0.272727272727273
18900.272727272727273-0.272727272727273
19000.642857142857143-0.642857142857143
19100.9875-0.9875
19200.642857142857143-0.642857142857143
19300.857142857142857-0.857142857142857
19400.642857142857143-0.642857142857143
19500.571428571428571-0.571428571428571



Parameters (Session):
par1 = 11 ; par2 = none ; par3 = 3 ; par4 = no ;
Parameters (R input):
par1 = 11 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
par4 <- 'no'
par3 <- '3'
par2 <- 'none'
par1 <- '10'
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}