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Tracking signal

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signal is then used as the value of the smoothing constant for the next forecast. The idea is that when the tracking signal is large, it suggests that the time series has undergone a shift; a larger value of the smoothing constant should be more responsive to a sudden shift in the underlying signal.
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There have also been proposed methods for adjusting the smoothing constants used in forecasting methods based on some measure of prior performance of the forecasting model. One such approach is suggested by Trigg and Leach (1967), which requires the calculation of the tracking signal. The tracking
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monitors any forecasts that have been made in comparison with actuals, and warns when there are unexpected departures of the outcomes from the forecasts. Forecasts can relate to sales, inventory, or anything pertaining to an organization's future demand.
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Mita Montero, J David (1973). "Análise de Sistemas de Previsão - Amortecimento Exponencial". Tese de Mestrado de Engenharia Industrial PUC-RJ, Brasil. Aplicação Industrial de Tracking Signal.
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The tracking signal is a simple indicator that forecast bias is present in the forecast model. It is most often used when the validity of the forecasting model might be in doubt.
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One form of tracking signal is the ratio of the cumulative sum of forecast errors (the deviations between the estimated forecasts and the actual values) to the
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greater than .51 indicates nonrandom errors. The tracking signal also can be used directly as a variable smoothing constant.
423: 345: 815: 340:| is the absolute value of the observed error. The smoothed values of the error and the absolute error are given by: 316:{\displaystyle {\text{Tracking signal}}={\frac {\Sigma (a_{t}-f_{t})}{{\frac {1}{n}}\Sigma \left|a_{t}-f_{t}\right|}}} 644: 638: 655: 129: 41: 810: 731:
Alstrom, P., Madsen, P. (1996) "Tracking signals in inventory control systems: A simulation study",
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Trigg, D.W. and Leach, A.G. (1967). "Exponential smoothing with an adaptive response rate".
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is the number of periods. Plugging this in, the entire formula for tracking signal is:
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Another proposed tracking signal was developed by Trigg (1964). In this model, e
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If no significant bias is present in the forecast, then the smoothed error
197:{\displaystyle {\text{MAD}}={\frac {\Sigma \left|a_{t}-f_{t}\right|}{n}}} 623: 698:
APICS Dictionary 12th Edition. Available for download at
566:{\displaystyle T_{t}=\left|{\frac {E_{t}}{M_{t}}}\right|} 582:
should be small compared to the smoothed absolute error
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is the actual value of the quantity being forecast, and
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Trigg, D.W. (1964) "Monitoring a forecasting system".
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by Tyler Hedin, Brigham Young University (Powerpoint)
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Production & Operations Analysis, Fifth Edition
412:{\displaystyle E_{t}=\beta e_{t}+(1-\beta )E_{t-1}} 700:http://www.apics.org/Resources/APICSDictionary.htm 565: 499: 411: 315: 196: 104: 790:Tracking Signal:A Measure of Forecast Accuracy 733:International Journal of Production Economics 8: 44:. The formula for this tracking signal is: 674:Learn how and when to remove this message 551: 541: 535: 522: 516: 485: 458: 452: 443: 431: 425: 397: 369: 353: 347: 299: 286: 264: 253: 240: 227: 219: 217: 177: 164: 149: 141: 139: 87: 74: 61: 53: 51: 637:This article includes a list of general 691: 509:Then the tracking signal is the ratio: 7: 806:Statistical deviation and dispersion 614:Calculating demand forecast accuracy 643:it lacks sufficient corresponding 274: 230: 152: 64: 14: 628: 329:is the observed error in period 768:Operational Research Quarterly 132:. The formula for the MAD is: 784:Tracking signal in forecasting 761:Operational Research Quarterly 478: 466: 459: 444: 390: 378: 259: 233: 93: 67: 1: 128:is the forecast. MAD is the 741:10.1016/0925-5273(95)00120-4 735:, 45 (1-3), 293–302, 837: 786:by Dr Muhammad Al-Salamah 593:of 0.1, a value of 821:Statistical forecasting 745:Nahmias, Steven (2005) 719:Nahmias (2005, page 97) 710:Nahmias (2005, page 89) 658:more precise citations. 130:mean absolute deviation 42:mean absolute deviation 567: 501: 413: 317: 198: 106: 770:, 18 (1), 53–59 568: 502: 414: 318: 199: 107: 763:, 15, 271–274. 515: 424: 346: 216: 138: 50: 816:Management science 619:Demand forecasting 563: 497: 409: 313: 194: 102: 22:management science 684: 683: 676: 557: 311: 272: 222: 192: 144: 100: 99: 56: 828: 720: 717: 711: 708: 702: 696: 679: 672: 668: 665: 659: 654:this article by 645:inline citations 632: 631: 624: 572: 570: 569: 564: 562: 558: 556: 555: 546: 545: 536: 527: 526: 506: 504: 503: 498: 496: 495: 462: 457: 456: 447: 436: 435: 418: 416: 415: 410: 408: 407: 374: 373: 358: 357: 322: 320: 319: 314: 312: 310: 309: 305: 304: 303: 291: 290: 273: 265: 262: 258: 257: 245: 244: 228: 223: 220: 203: 201: 200: 195: 193: 188: 187: 183: 182: 181: 169: 168: 150: 145: 142: 111: 109: 108: 103: 101: 97: 96: 92: 91: 79: 78: 62: 57: 54: 836: 835: 831: 830: 829: 827: 826: 825: 796: 795: 780: 749:, McGraw-Hill. 728: 723: 718: 714: 709: 705: 697: 693: 689: 680: 669: 663: 660: 650:Please help to 649: 633: 629: 610: 598: 587: 580: 547: 537: 531: 518: 513: 512: 481: 448: 427: 422: 421: 393: 365: 349: 344: 343: 338: 328: 295: 282: 281: 277: 263: 249: 236: 229: 221:Tracking signal 214: 213: 173: 160: 159: 155: 151: 136: 135: 126: 119: 83: 70: 63: 55:Tracking signal 48: 47: 38: 26:tracking signal 12: 11: 5: 834: 832: 824: 823: 818: 813: 808: 798: 797: 794: 793: 787: 779: 778:External links 776: 775: 774: 771: 764: 757: 743: 727: 724: 722: 721: 712: 703: 690: 688: 685: 682: 681: 664:September 2010 636: 634: 627: 622: 621: 616: 609: 606: 596: 585: 578: 561: 554: 550: 544: 540: 534: 530: 525: 521: 494: 491: 488: 484: 480: 477: 474: 471: 468: 465: 461: 455: 451: 446: 442: 439: 434: 430: 406: 403: 400: 396: 392: 389: 386: 383: 380: 377: 372: 368: 364: 361: 356: 352: 336: 326: 308: 302: 298: 294: 289: 285: 280: 276: 271: 268: 261: 256: 252: 248: 243: 239: 235: 232: 226: 191: 186: 180: 176: 172: 167: 163: 158: 154: 148: 124: 117: 95: 90: 86: 82: 77: 73: 69: 66: 60: 37: 34: 13: 10: 9: 6: 4: 3: 2: 833: 822: 819: 817: 814: 812: 809: 807: 804: 803: 801: 791: 788: 785: 782: 781: 777: 772: 769: 765: 762: 758: 756: 755:0-07-123837-9 752: 748: 744: 742: 738: 734: 730: 729: 725: 716: 713: 707: 704: 701: 695: 692: 686: 678: 675: 667: 657: 653: 647: 646: 640: 635: 626: 625: 620: 617: 615: 612: 611: 607: 605: 601: 599: 592: 588: 581: 573: 559: 552: 548: 542: 538: 532: 528: 523: 519: 510: 507: 492: 489: 486: 482: 475: 472: 469: 463: 453: 449: 440: 437: 432: 428: 419: 404: 401: 398: 394: 387: 384: 381: 375: 370: 366: 362: 359: 354: 350: 341: 339: 332: 323: 306: 300: 296: 292: 287: 283: 278: 269: 266: 254: 250: 246: 241: 237: 224: 211: 209: 204: 189: 184: 178: 174: 170: 165: 161: 156: 146: 133: 131: 127: 120: 112: 88: 84: 80: 75: 71: 58: 45: 43: 35: 33: 30: 27: 23: 19: 767: 760: 746: 732: 715: 706: 694: 670: 661: 642: 602: 594: 590: 583: 576: 574: 511: 508: 420: 342: 334: 330: 324: 212: 207: 205: 134: 122: 115: 113: 46: 39: 31: 25: 15: 811:Time series 656:introducing 800:Categories 726:References 639:references 36:Definition 18:statistics 490:− 476:β 473:− 441:β 402:− 388:β 385:− 363:β 293:− 275:Σ 247:− 231:Σ 171:− 153:Σ 81:− 65:Σ 608:See also 652:improve 753:  641:, but 206:where 114:where 687:Notes 333:and | 751:ISBN 24:, a 20:and 737:doi 143:MAD 98:MAD 16:In 802:: 739:: 677:) 671:( 666:) 662:( 648:. 597:t 595:T 591:β 586:t 584:M 579:t 577:E 560:| 553:t 549:M 543:t 539:E 533:| 529:= 524:t 520:T 493:1 487:t 483:M 479:) 470:1 467:( 464:+ 460:| 454:t 450:e 445:| 438:= 433:t 429:M 405:1 399:t 395:E 391:) 382:1 379:( 376:+ 371:t 367:e 360:= 355:t 351:E 337:t 335:e 331:t 327:t 307:| 301:t 297:f 288:t 284:a 279:| 270:n 267:1 260:) 255:t 251:f 242:t 238:a 234:( 225:= 208:n 190:n 185:| 179:t 175:f 166:t 162:a 157:| 147:= 125:t 123:f 118:t 116:a 94:) 89:t 85:f 76:t 72:a 68:( 59:=

Index

statistics
management science
mean absolute deviation
mean absolute deviation
Calculating demand forecast accuracy
Demand forecasting
references
inline citations
improve
introducing
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http://www.apics.org/Resources/APICSDictionary.htm
doi
10.1016/0925-5273(95)00120-4
ISBN
0-07-123837-9
Tracking signal in forecasting
Tracking Signal:A Measure of Forecast Accuracy
Categories
Statistical deviation and dispersion
Time series
Management science
Statistical forecasting

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