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Dominating decision rule

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411: 302: 134: 232: 205: 95: 68: 342: 322: 178: 158: 237: 452: 392: 445: 17: 104: 40:
another if the performance of the former is sometimes better, and never worse, than that of the latter.
471: 476: 438: 357: 426: 210: 183: 73: 46: 382: 327: 307: 163: 143: 8: 388: 410: 352: 98: 33: 422: 465: 348: 137: 418: 30: 297:{\displaystyle R(\theta ,\delta _{1})\leq R(\theta ,\delta _{2})} 330: 310: 240: 213: 186: 166: 146: 107: 76: 49: 384:Data Fusion in Robotics & Machine Intelligence 336: 316: 296: 226: 199: 172: 152: 128: 89: 62: 463: 446: 380: 27:Rule that is never worse and sometimes better 453: 439: 381:Abadi, Mongi; Gonzalez, Rafael C. (1992), 376: 374: 324:, and the inequality is strict for some 14: 464: 355:with respect to this order are called 371: 405: 24: 129:{\displaystyle R(\theta ,\delta )} 25: 488: 409: 387:, Academic Press, p. 227, 291: 272: 263: 244: 123: 111: 13: 1: 364: 207:is said to dominate the rule 36:, a decision rule is said to 425:. You can help Knowledge by 7: 227:{\displaystyle \delta _{2}} 200:{\displaystyle \delta _{1}} 90:{\displaystyle \delta _{2}} 63:{\displaystyle \delta _{1}} 10: 493: 404: 358:admissible decision rules 351:on decision rules; the 337:{\displaystyle \theta } 317:{\displaystyle \theta } 173:{\displaystyle \theta } 153:{\displaystyle \delta } 421:-related article is a 338: 318: 298: 228: 201: 174: 154: 130: 91: 64: 339: 319: 299: 229: 202: 175: 155: 131: 92: 65: 328: 308: 238: 211: 184: 180:. The decision rule 164: 144: 105: 74: 47: 334: 314: 294: 224: 197: 170: 150: 126: 87: 60: 434: 433: 16:(Redirected from 484: 472:Statistics stubs 455: 448: 441: 413: 406: 399: 397: 378: 353:maximal elements 343: 341: 340: 335: 323: 321: 320: 315: 303: 301: 300: 295: 290: 289: 262: 261: 233: 231: 230: 225: 223: 222: 206: 204: 203: 198: 196: 195: 179: 177: 176: 171: 159: 157: 156: 151: 135: 133: 132: 127: 96: 94: 93: 88: 86: 85: 69: 67: 66: 61: 59: 58: 21: 492: 491: 487: 486: 485: 483: 482: 481: 477:Decision theory 462: 461: 460: 459: 403: 402: 395: 379: 372: 367: 347:This defines a 329: 326: 325: 309: 306: 305: 285: 281: 257: 253: 239: 236: 235: 218: 214: 212: 209: 208: 191: 187: 185: 182: 181: 165: 162: 161: 145: 142: 141: 106: 103: 102: 81: 77: 75: 72: 71: 54: 50: 48: 45: 44: 34:decision theory 28: 23: 22: 15: 12: 11: 5: 490: 480: 479: 474: 458: 457: 450: 443: 435: 432: 431: 414: 401: 400: 393: 369: 368: 366: 363: 333: 313: 293: 288: 284: 280: 277: 274: 271: 268: 265: 260: 256: 252: 249: 246: 243: 221: 217: 194: 190: 169: 160:for parameter 149: 125: 122: 119: 116: 113: 110: 99:decision rules 84: 80: 57: 53: 43:Formally, let 26: 9: 6: 4: 3: 2: 489: 478: 475: 473: 470: 469: 467: 456: 451: 449: 444: 442: 437: 436: 430: 428: 424: 420: 415: 412: 408: 407: 396: 394:9780323138352 390: 386: 385: 377: 375: 370: 362: 361: 359: 354: 350: 349:partial order 345: 331: 311: 286: 282: 278: 275: 269: 266: 258: 254: 250: 247: 241: 219: 215: 192: 188: 167: 147: 139: 120: 117: 114: 108: 100: 82: 78: 55: 51: 41: 39: 35: 32: 19: 427:expanding it 416: 383: 356: 346: 42: 37: 29: 18:Nondominated 466:Categories 419:statistics 365:References 101:, and let 332:θ 312:θ 283:δ 276:θ 267:≤ 255:δ 248:θ 216:δ 189:δ 168:θ 148:δ 121:δ 115:θ 79:δ 52:δ 304:for all 140:of rule 38:dominate 136:be the 97:be two 391:  417:This 423:stub 389:ISBN 138:risk 70:and 234:if 468:: 373:^ 344:. 31:In 454:e 447:t 440:v 429:. 398:. 360:. 292:) 287:2 279:, 273:( 270:R 264:) 259:1 251:, 245:( 242:R 220:2 193:1 124:) 118:, 112:( 109:R 83:2 56:1 20:)

Index

Nondominated
In
decision theory
decision rules
risk
partial order
maximal elements
admissible decision rules


Data Fusion in Robotics & Machine Intelligence
ISBN
9780323138352
Stub icon
statistics
stub
expanding it
v
t
e
Categories
Statistics stubs
Decision theory

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