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  1. <Invariants model="com.necla.asds.engine.core.ARXWithCModelStable">
  2. <Invariant>
  3. <uName>FI202.F</uName>
  4. <yName>FIC103.PV</yName>
  5. <fitness>0.8556654806711218</fitness>
  6. <correlation>1.0</correlation>
  7. <validity>1.0</validity>
  8. <theta>-0.39560431960744163,-0.40996937790319876,-0.07381490654773078,0.0067978235099341935,0.026328112225060867,-0.010043078587020624,1.3837151730576487</theta>
  9. <n>2</n>
  10. <m>3</m>
  11. <k>0</k>
  12. <threshold>0.06391511945016919</threshold>
  13. <slope>0.0</slope>
  14. <intercept>0.0</intercept>
  15. </Invariant>
  16. <Invariant>
  17. <uName>FIC103.PV</uName>
  18. <yName>QIC401.SV</yName>
  19. <fitness>0.5645612423483941</fitness>
  20. <correlation>1.0</correlation>
  21. <validity>1.0</validity>
  22. <theta>-1.3850070330847704,0.4057557726890763,-0.592123814613997,-1.637011573058993,8.22975596501769,-5.447235442651117,-0.6036597233257712</theta>
  23. <n>2</n>
  24. <m>3</m>
  25. <k>0</k>
  26. <threshold>2.5085247071007024</threshold>
  27. <slope>0.0</slope>
  28. <intercept>0.0</intercept>
  29. </Invariant>
  30. <Invariant>
  31. <uName>QIC101.MV</uName>
  32. <yName>FIC103.PV</yName>
  33. <fitness>0.8528781036260125</fitness>
  34. <correlation>1.0</correlation>
  35. <validity>1.0</validity>
  36. <theta>-1.3045560882790561,0.36319451639725275,0.021166035393422853,-0.029173558234818882,0.0034838786184830206,0.005859313510228732,0.01690305497200445</theta>
  37. <n>2</n>
  38. <m>3</m>
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  40. <threshold>0.10075870410553196</threshold>
  41. <slope>0.0</slope>
  42. <intercept>0.0</intercept>
  43. </Invariant>
  44. <Invariant>
  45. <uName>FIC103.PV</uName>
  46. <yName>QI401.Q</yName>
  47. <fitness>0.564583237633956</fitness>
  48. <correlation>1.0</correlation>
  49. <validity>1.0</validity>
  50. <theta>-1.3853358226076564,0.40605133062406984,-0.576239286167973,-1.6864617470694574,8.29893044636345,-5.483705964438993,-0.6027232371883899</theta>
  51. <n>2</n>
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  55. <slope>0.0</slope>
  56. <intercept>0.0</intercept>
  57. </Invariant>
  58. <Invariant>
  59. <uName>PIC102.SV</uName>
  60. <yName>FIC103.PV</yName>
  61. <fitness>0.7842171999191965</fitness>
  62. <correlation>1.0</correlation>
  63. <validity>1.0</validity>
  64. <theta>-0.03658139409178105,-0.03605463311197836,8.307178140543974E-4,0.0017810202292737466,0.0015373187629170821,8.134533159570884E-4,-0.15819690211599371</theta>
  65. <n>2</n>
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  68. <threshold>0.15402684295331984</threshold>
  69. <slope>0.0</slope>
  70. <intercept>0.0</intercept>
  71. </Invariant>
  72. <Invariant>
  73. <uName>LIC201.MV</uName>
  74. <yName>FIC103.PV</yName>
  75. <fitness>0.9002373115521705</fitness>
  76. <correlation>1.0</correlation>
  77. <validity>1.0</validity>
  78. <theta>-0.03428354649211122,-0.016780614797735585,0.045605043880283656,-0.041937847709818656,-0.013759607785071189,0.030756643329427402,0.25220929891029487</theta>
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  83. <slope>0.0</slope>
  84. <intercept>0.0</intercept>
  85. </Invariant>
  86. <Invariant>
  87. <uName>FIC103.PV</uName>
  88. <yName>FIC101.MV</yName>
  89. <fitness>0.8786771459110492</fitness>
  90. <correlation>1.0</correlation>
  91. <validity>1.0</validity>
  92. <theta>-0.2938660935315242,-0.2850550755841386,-2.230920609122716,4.055582201585561,-1.953395160868713,20.030994856386585,-6.088928978643679</theta>
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  98. <intercept>0.0</intercept>
  99. </Invariant>
  100. <Invariant>
  101. <uName>TIC103.SV</uName>
  102. <yName>FIC103.PV</yName>
  103. <fitness>0.8577599207571457</fitness>
  104. <correlation>1.0</correlation>
  105. <validity>1.0</validity>
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  111. <slope>0.0</slope>
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  113. </Invariant>
  114. <Invariant>
  115. <uName>LIC301.MV</uName>
  116. <yName>FIC103.PV</yName>
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  118. <correlation>1.0</correlation>
  119. <validity>1.0</validity>
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  121. <n>2</n>
  122. <m>3</m>
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  124. <threshold>0.19819009942072618</threshold>
  125. <slope>0.0</slope>
  126. <intercept>0.0</intercept>
  127. </Invariant>
  128. <Invariant>
  129. <uName>FIC103.PV</uName>
  130. <yName>FI307.F</yName>
  131. <fitness>0.83054533290571</fitness>
  132. <correlation>1.0</correlation>
  133. <validity>1.0</validity>
  134. <theta>-0.2834127949271803,-0.2886765944662677,0.2179676996758306,-0.18065586590651672,-0.030097841934174936,0.06009596412970539,-0.05223149073238422</theta>
  135. <n>2</n>
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  139. <slope>0.0</slope>
  140. <intercept>0.0</intercept>
  141. </Invariant>
  142. <Invariant>
  143. <uName>FIC304.MV</uName>
  144. <yName>FIC103.PV</yName>
  145. <fitness>0.5172170568453338</fitness>
  146. <correlation>1.0</correlation>
  147. <validity>1.0</validity>
  148. <theta>-1.5006997317344093,0.5119303881895245,0.006113548902571621,-0.009247470944763228,0.0029233916872685676,0.0015067654301842391,-0.07671694071688236</theta>
  149. <n>2</n>
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  153. <slope>0.0</slope>
  154. <intercept>0.0</intercept>
  155. </Invariant>
  156. <Invariant>
  157. <uName>FIC103.PV</uName>
  158. <yName>FIC402.SV</yName>
  159. <fitness>0.691514261908249</fitness>
  160. <correlation>1.0</correlation>
  161. <validity>1.0</validity>
  162. <theta>1.1073774980362714,1.7382895348442844,0.1480660518509296</theta>
  163. <n>0</n>
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  166. <threshold>0.9294845907228957</threshold>
  167. <slope>0.0</slope>
  168. <intercept>0.0</intercept>
  169. </Invariant>
  170. <Invariant>
  171. <uName>FI252.F</uName>
  172. <yName>FIC103.PV</yName>
  173. <fitness>0.9425491748899908</fitness>
  174. <correlation>1.0</correlation>
  175. <validity>1.0</validity>
  176. <theta>-0.004920759181412361,9.121750694657752E-4,0.2926991059019302,-0.23378084260202053,0.0636217842915759,0.06409150913821227,-0.4844034837739736</theta>
  177. <n>2</n>
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  180. <threshold>0.11058184557508938</threshold>
  181. <slope>0.0</slope>
  182. <intercept>0.0</intercept>
  183. </Invariant>
  184. <Invariant>
  185. <uName>TIC301.MV</uName>
  186. <yName>QIC103.SV</yName>
  187. <fitness>0.999921656032696</fitness>
  188. <correlation>1.0</correlation>
  189. <validity>1.0</validity>
  190. <theta>3.1003997132369777E-19,21.599999999999998</theta>
  191. <n>0</n>
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  195. <slope>0.0</slope>
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  197. </Invariant>
  198. <Invariant>
  199. <uName>FIC305.PV</uName>
  200. <yName>FIC103.PV</yName>
  201. <fitness>0.8551937260852763</fitness>
  202. <correlation>1.0</correlation>
  203. <validity>1.0</validity>
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  205. <n>2</n>
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  210. <intercept>0.0</intercept>
  211. </Invariant>
  212. <Invariant>
  213. <uName>PIC101.PV</uName>
  214. <yName>FIC103.PV</yName>
  215. <fitness>0.7878480299142505</fitness>
  216. <correlation>1.0</correlation>
  217. <validity>1.0</validity>
  218. <theta>-0.5310417787410139,-0.46726574066437543,-0.00408017529251292,3.254009769607162E-4,0.00197181919355608,4.1952643431846393E-4,1.208698865206915</theta>
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  225. </Invariant>
  226. <Invariant>
  227. <uName>FIC103.PV</uName>
  228. <yName>FIC401.PV</yName>
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  239. </Invariant>
  240. <Invariant>
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  253. </Invariant>
  254. <Invariant>
  255. <uName>FIC103.PV</uName>
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  267. </Invariant>
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  281. </Invariant>
  282. <Invariant>
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  295. </Invariant>
  296. <Invariant>
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  309. </Invariant>
  310. <Invariant>
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  323. </Invariant>
  324. <Invariant>
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  337. </Invariant>
  338. <Invariant>
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  379. </Invariant>
  380. <Invariant>
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  393. </Invariant>
  394. <Invariant>
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  396. <yName>QIC401.SV</yName>
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  407. </Invariant>
  408. <Invariant>
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  410. <yName>QI301.Qs</yName>
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  421. </Invariant>
  422. <Invariant>
  423. <uName>FI252.F</uName>
  424. <yName>QIC105.SV</yName>
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  1949. <uName>QIC105.SV</uName>
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  1990. <Invariant>
  1991. <uName>FIC304.MV</uName>
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  2019. <uName>FI202.F</uName>
  2020. <yName>FIC101.MV</yName>
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