pols_50males_format0.Discriminant 13 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390
  1. File type = "ooTextFile"
  2. Object class = "Discriminant"
  3. numberOfEigenvalues = 3
  4. dimension = 3
  5. eigenvalues []:
  6. eigenvalues [1] = 21.139001553325844
  7. eigenvalues [2] = 4.355295817120748
  8. eigenvalues [3] = 0.6828853876561858
  9. eigenvectors [] []:
  10. eigenvectors [1]:
  11. eigenvectors [1] [1] = -0.4968246733001902
  12. eigenvectors [1] [2] = 0.7929232798703864
  13. eigenvectors [1] [3] = -0.35275758849349803
  14. eigenvectors [2]:
  15. eigenvectors [2] [1] = 0.8675540972437397
  16. eigenvectors [2] [2] = 0.46440535560029494
  17. eigenvectors [2] [3] = -0.17798189246483306
  18. eigenvectors [3]:
  19. eigenvectors [3] [1] = -0.022696527394271637
  20. eigenvectors [3] [2] = 0.39446208680854555
  21. eigenvectors [3] [3] = 0.9186318793264734
  22. numberOfGroups = 12
  23. groups? <exists>
  24. size = 12
  25. item []:
  26. item [1]:
  27. class = "SSCP"
  28. name = "\as"
  29. numberOfColumns = 3
  30. columnLabels []:
  31. "F1" "F2" "F3"
  32. numberOfRows = 3
  33. row [1]: "F1" 0.1371322072880503 0.06507801179217895 -0.011074735561417193
  34. row [2]: "F2" 0.06507801179217895 0.07640416821463858 -0.0019956280460737305
  35. row [3]: "F3" -0.011074735561417193 -0.0019956280460737305 0.04095240135530774
  36. numberOfObservations = 50
  37. centroid []:
  38. centroid [1] = 2.829041821512515
  39. centroid [2] = 3.0200046382498926
  40. centroid [3] = 3.4171619939756255
  41. item [2]:
  42. class = "SSCP"
  43. name = "\ct"
  44. numberOfColumns = 3
  45. columnLabels []:
  46. "F1" "F2" "F3"
  47. numberOfRows = 3
  48. row [1]: "F1" 0.09067302012389811 0.03716882530705852 0.010895111765093148
  49. row [2]: "F2" 0.03716882530705852 0.06623815158562135 -0.008040088713702414
  50. row [3]: "F3" 0.010895111765093148 -0.008040088713702414 0.047514137896571926
  51. numberOfObservations = 50
  52. centroid []:
  53. centroid [1] = 2.7164753792040868
  54. centroid [2] = 2.9358032337839095
  55. centroid [3] = 3.428957254834133
  56. item [3]:
  57. class = "SSCP"
  58. name = "\ep"
  59. numberOfColumns = 3
  60. columnLabels []:
  61. "F1" "F2" "F3"
  62. numberOfRows = 3
  63. row [1]: "F1" 0.12325126739884948 0.007977535637010664 0.014713593912108792
  64. row [2]: "F2" 0.007977535637010664 0.08256097042007325 0.05045318851511985
  65. row [3]: "F3" 0.014713593912108792 0.05045318851511985 0.07438879619774624
  66. numberOfObservations = 50
  67. centroid []:
  68. centroid [1] = 2.763135965884448
  69. centroid [2] = 3.2349692064700704
  70. centroid [3] = 3.391162711212973
  71. item [4]:
  72. class = "SSCP"
  73. name = "\ic"
  74. numberOfColumns = 3
  75. columnLabels []:
  76. "F1" "F2" "F3"
  77. numberOfRows = 3
  78. row [1]: "F1" 0.17647612299370122 -0.02063302628174945 -0.005697855587989537
  79. row [2]: "F2" -0.02063302628174945 0.07460647712948608 0.049614643436171904
  80. row [3]: "F3" -0.005697855587989537 0.049614643436171904 0.05109063361148622
  81. numberOfObservations = 50
  82. centroid []:
  83. centroid [1] = 2.585018518814506
  84. centroid [2] = 3.3000373347537915
  85. centroid [3] = 3.408994217433088
  86. item [5]:
  87. class = "SSCP"
  88. name = "\o/"
  89. numberOfColumns = 3
  90. columnLabels []:
  91. "F1" "F2" "F3"
  92. numberOfRows = 3
  93. row [1]: "F1" 0.09908822912163297 0.015541819671631943 0.013775375020258235
  94. row [2]: "F2" 0.015541819671631943 0.056684926460000895 0.025520496405190735
  95. row [3]: "F3" 0.013775375020258235 0.025520496405190735 0.03527931367299332
  96. numberOfObservations = 50
  97. centroid []:
  98. centroid [1] = 2.643922974695668
  99. centroid [2] = 3.174039321160438
  100. centroid [3] = 3.353368431962918
  101. item [6]:
  102. class = "SSCP"
  103. name = "\yc"
  104. numberOfColumns = 3
  105. columnLabels []:
  106. "F1" "F2" "F3"
  107. numberOfRows = 3
  108. row [1]: "F1" 0.11604848853561119 0.004638097797573026 0.014234726305389083
  109. row [2]: "F2" 0.004638097797573026 0.08910829880242509 0.05772847540761414
  110. row [3]: "F3" 0.014234726305389083 0.05772847540761414 0.059535232541858635
  111. numberOfObservations = 50
  112. centroid []:
  113. centroid [1] = 2.638814682287954
  114. centroid [2] = 3.1732312476628675
  115. centroid [3] = 3.3702977370451324
  116. item [7]:
  117. class = "SSCP"
  118. name = "a"
  119. numberOfColumns = 3
  120. columnLabels []:
  121. "F1" "F2" "F3"
  122. numberOfRows = 3
  123. row [1]: "F1" 0.13373820303933756 0.043918895913021325 0.009483926777506332
  124. row [2]: "F2" 0.043918895913021325 0.07185378889695229 0.017946300429884602
  125. row [3]: "F3" 0.009483926777506332 0.017946300429884602 0.056974025547855855
  126. numberOfObservations = 50
  127. centroid []:
  128. centroid [1] = 2.8971834611872826
  129. centroid [2] = 3.1126947721089406
  130. centroid [3] = 3.407776548856642
  131. item [8]:
  132. class = "SSCP"
  133. name = "e"
  134. numberOfColumns = 3
  135. columnLabels []:
  136. "F1" "F2" "F3"
  137. numberOfRows = 3
  138. row [1]: "F1" 0.16197482567602983 0.002298374666522604 0.012604046776579057
  139. row [2]: "F2" 0.002298374666522604 0.061562730940411266 0.04116004354455001
  140. row [3]: "F3" 0.012604046776579057 0.04116004354455001 0.043223685110515324
  141. numberOfObservations = 50
  142. centroid []:
  143. centroid [1] = 2.606165152281404
  144. centroid [2] = 3.3033427054078994
  145. centroid [3] = 3.406164846453073
  146. item [9]:
  147. class = "SSCP"
  148. name = "i"
  149. numberOfColumns = 3
  150. columnLabels []:
  151. "F1" "F2" "F3"
  152. numberOfRows = 3
  153. row [1]: "F1" 0.15428266876841684 0.013276386826015094 0.012320309785365528
  154. row [2]: "F2" 0.013276386826015094 0.055510083642718484 0.03784952638535774
  155. row [3]: "F3" 0.012320309785365528 0.03784952638535774 0.05006027585038744
  156. numberOfObservations = 50
  157. centroid []:
  158. centroid [1] = 2.464795953065796
  159. centroid [2] = 3.3427245505456598
  160. centroid [3] = 3.4407579626513725
  161. item [10]:
  162. class = "SSCP"
  163. name = "o"
  164. numberOfColumns = 3
  165. columnLabels []:
  166. "F1" "F2" "F3"
  167. numberOfRows = 3
  168. row [1]: "F1" 0.06861045715394555 0.035093223137004324 -0.0023606822102749565
  169. row [2]: "F2" 0.035093223137004324 0.09021650740495563 0.006512208041729222
  170. row [3]: "F3" -0.0023606822102749565 0.006512208041729222 0.07700471610942107
  171. numberOfObservations = 50
  172. centroid []:
  173. centroid [1] = 2.6855835642500985
  174. centroid [2] = 2.9572369144661237
  175. centroid [3] = 3.392825472161562
  176. item [11]:
  177. class = "SSCP"
  178. name = "u"
  179. numberOfColumns = 3
  180. columnLabels []:
  181. "F1" "F2" "F3"
  182. numberOfRows = 3
  183. row [1]: "F1" 0.1699999779614091 0.021885675183543243 0.0161142422435738
  184. row [2]: "F2" 0.021885675183543243 0.1039591160562141 -0.00200153380888963
  185. row [3]: "F3" 0.0161142422435738 -0.00200153380888963 0.07540959694619889
  186. numberOfObservations = 50
  187. centroid []:
  188. centroid [1] = 2.5268057305429337
  189. centroid [2] = 2.9058781887555085
  190. centroid [3] = 3.3643364436087393
  191. item [12]:
  192. class = "SSCP"
  193. name = "y"
  194. numberOfColumns = 3
  195. columnLabels []:
  196. "F1" "F2" "F3"
  197. numberOfRows = 3
  198. row [1]: "F1" 0.18909356327139404 0.014010234547664086 0.020273089008566562
  199. row [2]: "F2" 0.014010234547664086 0.0734940861707178 0.054864607563280654
  200. row [3]: "F3" 0.020273089008566562 0.054864607563280654 0.08826214244880358
  201. numberOfObservations = 50
  202. centroid []:
  203. centroid [1] = 2.4797538722099293
  204. centroid [2] = 3.236360871766193
  205. centroid [3] = 3.341855942791658
  206. total? <exists>
  207. numberOfColumns = 3
  208. columnLabels []:
  209. "F1" "F2" "F3"
  210. numberOfRows = 3
  211. row [1]: "F1" 11.43514736353313 -3.8028772011835716 0.7254293171774202
  212. row [2]: "F2" -3.8028772011835716 13.851776134183913 0.4932432271899076
  213. row [3]: "F3" 0.7254293171774202 0.4932432271899076 1.2160403917859772
  214. numberOfObservations = 600
  215. centroid []:
  216. centroid [1] = 2.6530580896613785
  217. centroid [2] = 3.141360248760944
  218. centroid [3] = 3.3936382969155714
  219. aprioriProbabilities []:
  220. aprioriProbabilities [1] = 0.08333333333333333
  221. aprioriProbabilities [2] = 0.08333333333333333
  222. aprioriProbabilities [3] = 0.08333333333333333
  223. aprioriProbabilities [4] = 0.08333333333333333
  224. aprioriProbabilities [5] = 0.08333333333333333
  225. aprioriProbabilities [6] = 0.08333333333333333
  226. aprioriProbabilities [7] = 0.08333333333333333
  227. aprioriProbabilities [8] = 0.08333333333333333
  228. aprioriProbabilities [9] = 0.08333333333333333
  229. aprioriProbabilities [10] = 0.08333333333333333
  230. aprioriProbabilities [11] = 0.08333333333333333
  231. aprioriProbabilities [12] = 0.08333333333333333
  232. costs [] []:
  233. costs [1]:
  234. costs [1] [1] = 0
  235. costs [1] [2] = 1
  236. costs [1] [3] = 1
  237. costs [1] [4] = 1
  238. costs [1] [5] = 1
  239. costs [1] [6] = 1
  240. costs [1] [7] = 1
  241. costs [1] [8] = 1
  242. costs [1] [9] = 1
  243. costs [1] [10] = 1
  244. costs [1] [11] = 1
  245. costs [1] [12] = 1
  246. costs [2]:
  247. costs [2] [1] = 1
  248. costs [2] [2] = 0
  249. costs [2] [3] = 1
  250. costs [2] [4] = 1
  251. costs [2] [5] = 1
  252. costs [2] [6] = 1
  253. costs [2] [7] = 1
  254. costs [2] [8] = 1
  255. costs [2] [9] = 1
  256. costs [2] [10] = 1
  257. costs [2] [11] = 1
  258. costs [2] [12] = 1
  259. costs [3]:
  260. costs [3] [1] = 1
  261. costs [3] [2] = 1
  262. costs [3] [3] = 0
  263. costs [3] [4] = 1
  264. costs [3] [5] = 1
  265. costs [3] [6] = 1
  266. costs [3] [7] = 1
  267. costs [3] [8] = 1
  268. costs [3] [9] = 1
  269. costs [3] [10] = 1
  270. costs [3] [11] = 1
  271. costs [3] [12] = 1
  272. costs [4]:
  273. costs [4] [1] = 1
  274. costs [4] [2] = 1
  275. costs [4] [3] = 1
  276. costs [4] [4] = 0
  277. costs [4] [5] = 1
  278. costs [4] [6] = 1
  279. costs [4] [7] = 1
  280. costs [4] [8] = 1
  281. costs [4] [9] = 1
  282. costs [4] [10] = 1
  283. costs [4] [11] = 1
  284. costs [4] [12] = 1
  285. costs [5]:
  286. costs [5] [1] = 1
  287. costs [5] [2] = 1
  288. costs [5] [3] = 1
  289. costs [5] [4] = 1
  290. costs [5] [5] = 0
  291. costs [5] [6] = 1
  292. costs [5] [7] = 1
  293. costs [5] [8] = 1
  294. costs [5] [9] = 1
  295. costs [5] [10] = 1
  296. costs [5] [11] = 1
  297. costs [5] [12] = 1
  298. costs [6]:
  299. costs [6] [1] = 1
  300. costs [6] [2] = 1
  301. costs [6] [3] = 1
  302. costs [6] [4] = 1
  303. costs [6] [5] = 1
  304. costs [6] [6] = 0
  305. costs [6] [7] = 1
  306. costs [6] [8] = 1
  307. costs [6] [9] = 1
  308. costs [6] [10] = 1
  309. costs [6] [11] = 1
  310. costs [6] [12] = 1
  311. costs [7]:
  312. costs [7] [1] = 1
  313. costs [7] [2] = 1
  314. costs [7] [3] = 1
  315. costs [7] [4] = 1
  316. costs [7] [5] = 1
  317. costs [7] [6] = 1
  318. costs [7] [7] = 0
  319. costs [7] [8] = 1
  320. costs [7] [9] = 1
  321. costs [7] [10] = 1
  322. costs [7] [11] = 1
  323. costs [7] [12] = 1
  324. costs [8]:
  325. costs [8] [1] = 1
  326. costs [8] [2] = 1
  327. costs [8] [3] = 1
  328. costs [8] [4] = 1
  329. costs [8] [5] = 1
  330. costs [8] [6] = 1
  331. costs [8] [7] = 1
  332. costs [8] [8] = 0
  333. costs [8] [9] = 1
  334. costs [8] [10] = 1
  335. costs [8] [11] = 1
  336. costs [8] [12] = 1
  337. costs [9]:
  338. costs [9] [1] = 1
  339. costs [9] [2] = 1
  340. costs [9] [3] = 1
  341. costs [9] [4] = 1
  342. costs [9] [5] = 1
  343. costs [9] [6] = 1
  344. costs [9] [7] = 1
  345. costs [9] [8] = 1
  346. costs [9] [9] = 0
  347. costs [9] [10] = 1
  348. costs [9] [11] = 1
  349. costs [9] [12] = 1
  350. costs [10]:
  351. costs [10] [1] = 1
  352. costs [10] [2] = 1
  353. costs [10] [3] = 1
  354. costs [10] [4] = 1
  355. costs [10] [5] = 1
  356. costs [10] [6] = 1
  357. costs [10] [7] = 1
  358. costs [10] [8] = 1
  359. costs [10] [9] = 1
  360. costs [10] [10] = 0
  361. costs [10] [11] = 1
  362. costs [10] [12] = 1
  363. costs [11]:
  364. costs [11] [1] = 1
  365. costs [11] [2] = 1
  366. costs [11] [3] = 1
  367. costs [11] [4] = 1
  368. costs [11] [5] = 1
  369. costs [11] [6] = 1
  370. costs [11] [7] = 1
  371. costs [11] [8] = 1
  372. costs [11] [9] = 1
  373. costs [11] [10] = 1
  374. costs [11] [11] = 0
  375. costs [11] [12] = 1
  376. costs [12]:
  377. costs [12] [1] = 1
  378. costs [12] [2] = 1
  379. costs [12] [3] = 1
  380. costs [12] [4] = 1
  381. costs [12] [5] = 1
  382. costs [12] [6] = 1
  383. costs [12] [7] = 1
  384. costs [12] [8] = 1
  385. costs [12] [9] = 1
  386. costs [12] [10] = 1
  387. costs [12] [11] = 1
  388. costs [12] [12] = 0