Knowledge (XXG)

Weight function

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is a mathematical device used when performing a sum, integral, or average to give some elements more "weight" or influence on the result than other elements in the same set. The result of this application of a weight function is a
2407: 2027: 728: 1160: 2296: 1538: 619: 2212: 2176: 998:. More generally, the expected value of a function of a random variable is the probability-weighted average of the values the function takes on for each possible value of the random variable. 1620: 372: 109: 1752: 950: 219: 2494: 1685: 443: 889: 1307: 2041: 1105: 531: 325: 1916: 57:. Weight functions can be employed in both discrete and continuous settings. They can be used to construct systems of calculus called "weighted calculus" and "meta-calculus". 1415: 833: 1815: 1356: 1944: 1847: 1435: 1379: 178: 984: 798: 1574: 1493: 1775: 1177: 1055: 771: 273: 253: 135: 1470: 2307: 1955: 637: 1017:
function is estimated, this function being a weighted average of the current and various lagged independent variable values. Similarly, a
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of a random variable is the weighted average of the possible values it might take on, with the weights being the respective
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specifies an evolving variable as a weighted average of current and various lagged values of a random variable.
190: 897: 1642: 388: 2551: 2127:{\displaystyle {\frac {\displaystyle \int _{\Omega }f(x)\,w(x)\,dx}{\displaystyle \int _{\Omega }w(x)\,dx}}} 1283: 839: 2413: 1438: 1064: 488: 282: 2459: 2434: 1870: 1627: 1544: 1319: 449: 226: 184:
situation in which all elements have equal weight. One can then apply this weight to various concepts.
54: 50: 1391: 2417: 1018: 1010: 806: 112: 2454: 379: 2449: 1006: 955: 2523: 2500: 1784: 1325: 1002: 750: 115: 1929: 1832: 1420: 1364: 835:, the best estimate of the signal is obtained by averaging all the measurements with weight 148: 1496: 629: 42: 962: 776: 2474: 1550: 1386: 1269:{\displaystyle {\frac {\sum _{i=1}^{n}w_{i}{\boldsymbol {x}}_{i}}{\sum _{i=1}^{n}w_{i}}},} 1014: 1475: 2429: 1760: 1169: 1040: 991: 756: 258: 238: 120: 1443: 2540: 2444: 2439: 2215: 625: 1623: 995: 893:
and the resulting variance is smaller than each of the independent measurements
468: 222: 1541: 746: 541: 460: 138: 46: 2402:{\displaystyle {\langle f,g\rangle }_{w}:=\int _{\Omega }f(x)g(x)\ w(x)\ dx.} 2469: 1034: 232: 142: 17: 2022:{\displaystyle {\frac {1}{\mathrm {vol} (\Omega )}}\int _{\Omega }f(x)\ dx} 1009:
is assumed to be affected by both current and lagged (past) values of the
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method weights the difference between fit and data using the same weights
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has finite non-zero weighted volume, then we can replace the unweighted
1947: 1577: 549: 1850: 1382: 1108: 723:{\displaystyle {\frac {\sum _{a\in A}f(a)w(a)}{\sum _{a\in A}w(a)}}.} 1155:{\displaystyle {\boldsymbol {x}}_{1},\dotsc ,{\boldsymbol {x}}_{n}} 1165: 1058: 2496:
The First Systems of Weighted Differential and Integral Calculus
2291:{\displaystyle \langle f,g\rangle :=\int _{\Omega }f(x)g(x)\ dx} 545: 1111:
is now interpreted in the physical sense) and locations
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are two functions, one can generalize the unweighted
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which is also the weighted average of the positions
1533:{\displaystyle w\colon \Omega \to \mathbb {R} ^{+}} 2401: 2290: 2206: 2170: 2126: 2021: 1938: 1910: 1841: 1809: 1769: 1746: 1679: 1614: 1568: 1532: 1487: 1464: 1429: 1409: 1373: 1350: 1318:In the continuous setting, a weight is a positive 1301: 1268: 1154: 1099: 1049: 978: 944: 883: 827: 792: 765: 722: 614:{\displaystyle {\frac {1}{|A|}}\sum _{a\in A}f(a)} 613: 525: 448:One common application of weighted sums arises in 437: 366: 319: 267: 247: 213: 172: 129: 103: 2207:{\displaystyle g\colon \Omega \to {\mathbb {R} }} 2171:{\displaystyle f\colon \Omega \to {\mathbb {R} }} 1615:{\displaystyle f\colon \Omega \to \mathbb {R} } 29:Construct related to weighted sums and averages 2493:Jane Grossman, Michael Grossman, Robert Katz. 544:non-empty set, one can replace the unweighted 53:, and are closely related to the concept of a 367:{\displaystyle w\colon A\to \mathbb {R} ^{+}} 104:{\displaystyle w\colon A\to \mathbb {R} ^{+}} 8: 2325: 2313: 2239: 2227: 1747:{\displaystyle \int _{\Omega }f(x)w(x)\,dx} 70:In the discrete setting, a weight function 2342: 2329: 2312: 2309: 2249: 2225: 2199: 2198: 2197: 2183: 2163: 2162: 2161: 2147: 2114: 2096: 2083: 2070: 2052: 2045: 2043: 1992: 1965: 1959: 1957: 1931: 1878: 1872: 1834: 1817:in order for this integral to be finite. 1800: 1786: 1762: 1737: 1707: 1701: 1650: 1644: 1608: 1607: 1593: 1552: 1524: 1520: 1519: 1504: 1477: 1445: 1422: 1401: 1397: 1396: 1393: 1366: 1341: 1327: 1293: 1288: 1285: 1254: 1244: 1233: 1221: 1216: 1209: 1199: 1188: 1181: 1179: 1164:then the lever will be in balance if the 1146: 1141: 1125: 1120: 1117: 1091: 1072: 1066: 1042: 970: 964: 945:{\textstyle \sigma ^{2}=1/\sum _{i}w_{i}} 936: 926: 917: 905: 899: 874: 869: 864: 859: 847: 841: 819: 814: 808: 784: 778: 758: 690: 648: 641: 639: 587: 575: 567: 561: 559: 496: 490: 396: 390: 358: 354: 353: 338: 290: 284: 260: 240: 214:{\displaystyle f\colon A\to \mathbb {R} } 207: 206: 192: 150: 122: 95: 91: 90: 75: 2519:Meta-Calculus: Differential and Integral 1547:. In this context, the weight function 2486: 1680:{\displaystyle \int _{\Omega }f(x)\ dx} 1289: 1217: 1142: 1121: 438:{\displaystyle \sum _{a\in A}f(a)w(a).} 45:. Weight functions occur frequently in 884:{\textstyle w_{i}=1/{\sigma _{i}^{2}}} 1302:{\displaystyle {\boldsymbol {x}}_{i}} 7: 773:measured multiple independent times 745:Weighted means are commonly used in 111:is a positive function defined on a 1100:{\displaystyle w_{1},\ldots ,w_{n}} 526:{\displaystyle \sum _{a\in B}w(a).} 320:{\displaystyle \sum _{a\in A}f(a);} 2343: 2250: 2191: 2155: 2097: 2053: 1993: 1979: 1972: 1969: 1966: 1933: 1911:{\displaystyle \int _{E}w(x)\ dx,} 1836: 1757:Note that one may need to require 1708: 1651: 1601: 1512: 1424: 1368: 749:to compensate for the presence of 25: 467:, one can replace the unweighted 1410:{\displaystyle \mathbb {R} ^{n}} 828:{\displaystyle \sigma _{i}^{2}} 2384: 2378: 2369: 2363: 2357: 2351: 2276: 2270: 2264: 2258: 2194: 2158: 2111: 2105: 2080: 2074: 2067: 2061: 2007: 2001: 1982: 1976: 1893: 1887: 1797: 1791: 1734: 1728: 1722: 1716: 1665: 1659: 1604: 1576:is sometimes referred to as a 1563: 1557: 1515: 1459: 1447: 1338: 1332: 711: 705: 681: 675: 669: 663: 608: 602: 576: 568: 517: 511: 429: 423: 417: 411: 349: 311: 305: 203: 161: 155: 86: 1: 2301:to a weighted bilinear form 1037:: if one has a collection of 1781:with respect to the weight 2583: 2557:Combinatorial optimization 2465:Riemann–Stieltjes integral 1861:can be generalized to the 1690:can be generalized to the 2416:for examples of weighted 1810:{\displaystyle w(x)\,dx} 1351:{\displaystyle w(x)\,dx} 1939:{\displaystyle \Omega } 1842:{\displaystyle \Omega } 1430:{\displaystyle \Omega } 1381:, which is typically a 1374:{\displaystyle \Omega } 1168:of the lever is at the 173:{\displaystyle w(a):=1} 145:. The weight function 2414:orthogonal polynomials 2403: 2292: 2208: 2172: 2128: 2023: 1940: 1912: 1843: 1811: 1771: 1748: 1681: 1616: 1570: 1534: 1489: 1466: 1431: 1411: 1375: 1352: 1303: 1270: 1249: 1204: 1156: 1101: 1051: 980: 946: 885: 829: 794: 767: 737:weights are relevant. 733:In this case only the 724: 615: 527: 439: 368: 321: 269: 249: 215: 174: 131: 105: 2547:Mathematical analysis 2460:Measure (mathematics) 2435:Numerical integration 2404: 2293: 2209: 2173: 2129: 2024: 1941: 1913: 1844: 1812: 1779:absolutely integrable 1772: 1749: 1682: 1617: 1571: 1535: 1490: 1467: 1432: 1412: 1376: 1353: 1304: 1271: 1229: 1184: 1157: 1102: 1052: 981: 979:{\displaystyle w_{i}} 947: 886: 830: 795: 793:{\displaystyle f_{i}} 768: 725: 616: 528: 450:numerical integration 440: 369: 322: 270: 250: 216: 175: 137:, which is typically 132: 106: 2418:orthogonal functions 2308: 2224: 2182: 2146: 2042: 1956: 1930: 1871: 1833: 1785: 1761: 1700: 1643: 1592: 1569:{\displaystyle w(x)} 1551: 1503: 1476: 1444: 1421: 1392: 1365: 1326: 1284: 1178: 1116: 1065: 1041: 1019:moving average model 1011:independent variable 963: 898: 840: 807: 777: 757: 638: 558: 489: 481:weighted cardinality 389: 337: 283: 259: 239: 191: 149: 121: 74: 2562:Functional analysis 2455:Kernel (statistics) 879: 824: 380:conical combination 180:corresponds to the 2567:Types of functions 2450:Linear combination 2399: 2288: 2204: 2168: 2124: 2121: 2090: 2019: 1936: 1908: 1839: 1807: 1767: 1744: 1677: 1612: 1584:General definition 1566: 1540:is a non-negative 1530: 1488:{\displaystyle dx} 1485: 1462: 1427: 1407: 1371: 1348: 1314:Continuous weights 1299: 1266: 1152: 1097: 1047: 1007:dependent variable 976: 956:maximum likelihood 942: 931: 881: 865: 825: 810: 790: 763: 753:. For a quantity 720: 701: 659: 611: 598: 523: 507: 435: 407: 364: 317: 301: 265: 245: 211: 170: 127: 101: 66:General definition 2412:See the entry on 2389: 2374: 2281: 2122: 2012: 1986: 1898: 1770:{\displaystyle f} 1692:weighted integral 1670: 1261: 1050:{\displaystyle n} 922: 766:{\displaystyle f} 715: 686: 644: 583: 581: 492: 392: 286: 268:{\displaystyle A} 248:{\displaystyle f} 130:{\displaystyle A} 16:(Redirected from 2574: 2531: 2514: 2508: 2491: 2408: 2406: 2405: 2400: 2387: 2372: 2347: 2346: 2334: 2333: 2328: 2297: 2295: 2294: 2289: 2279: 2254: 2253: 2213: 2211: 2210: 2205: 2203: 2202: 2177: 2175: 2174: 2169: 2167: 2166: 2133: 2131: 2130: 2125: 2123: 2101: 2100: 2057: 2056: 2046: 2034:weighted average 2028: 2026: 2025: 2020: 2010: 1997: 1996: 1987: 1985: 1975: 1960: 1945: 1943: 1942: 1937: 1922:Weighted average 1917: 1915: 1914: 1909: 1896: 1883: 1882: 1848: 1846: 1845: 1840: 1816: 1814: 1813: 1808: 1776: 1774: 1773: 1768: 1753: 1751: 1750: 1745: 1712: 1711: 1686: 1684: 1683: 1678: 1668: 1655: 1654: 1621: 1619: 1618: 1613: 1611: 1575: 1573: 1572: 1567: 1539: 1537: 1536: 1531: 1529: 1528: 1523: 1497:Lebesgue measure 1494: 1492: 1491: 1486: 1471: 1469: 1468: 1465:{\displaystyle } 1463: 1436: 1434: 1433: 1428: 1416: 1414: 1413: 1408: 1406: 1405: 1400: 1380: 1378: 1377: 1372: 1357: 1355: 1354: 1349: 1310: 1308: 1306: 1305: 1300: 1298: 1297: 1292: 1275: 1273: 1272: 1267: 1262: 1260: 1259: 1258: 1248: 1243: 1227: 1226: 1225: 1220: 1214: 1213: 1203: 1198: 1182: 1163: 1161: 1159: 1158: 1153: 1151: 1150: 1145: 1130: 1129: 1124: 1106: 1104: 1103: 1098: 1096: 1095: 1077: 1076: 1056: 1054: 1053: 1048: 1029:The terminology 987: 985: 983: 982: 977: 975: 974: 953: 951: 949: 948: 943: 941: 940: 930: 921: 910: 909: 892: 890: 888: 887: 882: 880: 878: 873: 863: 852: 851: 834: 832: 831: 826: 823: 818: 799: 797: 796: 791: 789: 788: 772: 770: 769: 764: 729: 727: 726: 721: 716: 714: 700: 684: 658: 642: 630:weighted average 620: 618: 617: 612: 597: 582: 580: 579: 571: 562: 532: 530: 529: 524: 506: 444: 442: 441: 436: 406: 373: 371: 370: 365: 363: 362: 357: 326: 324: 323: 318: 300: 274: 272: 271: 266: 254: 252: 251: 246: 220: 218: 217: 212: 210: 187:If the function 179: 177: 176: 171: 136: 134: 133: 128: 110: 108: 107: 102: 100: 99: 94: 61:Discrete weights 43:weighted average 21: 2582: 2581: 2577: 2576: 2575: 2573: 2572: 2571: 2537: 2536: 2535: 2534: 2515: 2511: 2492: 2488: 2483: 2475:Window function 2426: 2338: 2311: 2306: 2305: 2245: 2222: 2221: 2180: 2179: 2144: 2143: 2140: 2092: 2048: 2040: 2039: 1988: 1964: 1954: 1953: 1928: 1927: 1924: 1874: 1869: 1868: 1863:weighted volume 1831: 1830: 1829:is a subset of 1823: 1821:Weighted volume 1783: 1782: 1759: 1758: 1703: 1698: 1697: 1646: 1641: 1640: 1590: 1589: 1586: 1549: 1548: 1518: 1501: 1500: 1474: 1473: 1442: 1441: 1419: 1418: 1417:, for instance 1395: 1390: 1389: 1387:Euclidean space 1363: 1362: 1324: 1323: 1316: 1287: 1282: 1281: 1280: 1250: 1228: 1215: 1205: 1183: 1176: 1175: 1140: 1119: 1114: 1113: 1112: 1087: 1068: 1063: 1062: 1061:, with weights 1039: 1038: 1031:weight function 1027: 1015:distributed lag 966: 961: 960: 959: 932: 901: 896: 895: 894: 843: 838: 837: 836: 805: 804: 780: 775: 774: 755: 754: 743: 685: 643: 636: 635: 566: 556: 555: 487: 486: 387: 386: 352: 335: 334: 332:weight function 281: 280: 257: 256: 237: 236: 189: 188: 147: 146: 119: 118: 89: 72: 71: 68: 63: 34:weight function 30: 23: 22: 15: 12: 11: 5: 2580: 2578: 2570: 2569: 2564: 2559: 2554: 2552:Measure theory 2549: 2539: 2538: 2533: 2532: 2516:Jane Grossman. 2509: 2485: 2484: 2482: 2479: 2478: 2477: 2472: 2467: 2462: 2457: 2452: 2447: 2442: 2437: 2432: 2430:Center of mass 2425: 2422: 2410: 2409: 2398: 2395: 2392: 2386: 2383: 2380: 2377: 2371: 2368: 2365: 2362: 2359: 2356: 2353: 2350: 2345: 2341: 2337: 2332: 2327: 2324: 2321: 2318: 2315: 2299: 2298: 2287: 2284: 2278: 2275: 2272: 2269: 2266: 2263: 2260: 2257: 2252: 2248: 2244: 2241: 2238: 2235: 2232: 2229: 2201: 2196: 2193: 2190: 2187: 2165: 2160: 2157: 2154: 2151: 2139: 2136: 2135: 2134: 2120: 2117: 2113: 2110: 2107: 2104: 2099: 2095: 2089: 2086: 2082: 2079: 2076: 2073: 2069: 2066: 2063: 2060: 2055: 2051: 2030: 2029: 2018: 2015: 2009: 2006: 2003: 2000: 1995: 1991: 1984: 1981: 1978: 1974: 1971: 1968: 1963: 1935: 1923: 1920: 1919: 1918: 1907: 1904: 1901: 1895: 1892: 1889: 1886: 1881: 1877: 1838: 1822: 1819: 1806: 1803: 1799: 1796: 1793: 1790: 1766: 1755: 1754: 1743: 1740: 1736: 1733: 1730: 1727: 1724: 1721: 1718: 1715: 1710: 1706: 1688: 1687: 1676: 1673: 1667: 1664: 1661: 1658: 1653: 1649: 1610: 1606: 1603: 1600: 1597: 1585: 1582: 1565: 1562: 1559: 1556: 1527: 1522: 1517: 1514: 1511: 1508: 1484: 1481: 1461: 1458: 1455: 1452: 1449: 1426: 1404: 1399: 1370: 1347: 1344: 1340: 1337: 1334: 1331: 1315: 1312: 1296: 1291: 1277: 1276: 1265: 1257: 1253: 1247: 1242: 1239: 1236: 1232: 1224: 1219: 1212: 1208: 1202: 1197: 1194: 1191: 1187: 1170:center of mass 1149: 1144: 1139: 1136: 1133: 1128: 1123: 1094: 1090: 1086: 1083: 1080: 1075: 1071: 1046: 1026: 1023: 992:expected value 973: 969: 939: 935: 929: 925: 920: 916: 913: 908: 904: 877: 872: 868: 862: 858: 855: 850: 846: 822: 817: 813: 787: 783: 762: 742: 739: 731: 730: 719: 713: 710: 707: 704: 699: 696: 693: 689: 683: 680: 677: 674: 671: 668: 665: 662: 657: 654: 651: 647: 622: 621: 610: 607: 604: 601: 596: 593: 590: 586: 578: 574: 570: 565: 534: 533: 522: 519: 516: 513: 510: 505: 502: 499: 495: 446: 445: 434: 431: 428: 425: 422: 419: 416: 413: 410: 405: 402: 399: 395: 382:is defined as 361: 356: 351: 348: 345: 342: 328: 327: 316: 313: 310: 307: 304: 299: 296: 293: 289: 276:is defined as 264: 244: 209: 205: 202: 199: 196: 169: 166: 163: 160: 157: 154: 126: 98: 93: 88: 85: 82: 79: 67: 64: 62: 59: 28: 24: 14: 13: 10: 9: 6: 4: 3: 2: 2579: 2568: 2565: 2563: 2560: 2558: 2555: 2553: 2550: 2548: 2545: 2544: 2542: 2529: 2528:0-9771170-2-2 2525: 2521: 2520: 2513: 2510: 2506: 2505:0-9771170-1-4 2502: 2498: 2497: 2490: 2487: 2480: 2476: 2473: 2471: 2468: 2466: 2463: 2461: 2458: 2456: 2453: 2451: 2448: 2446: 2445:Weighted mean 2443: 2441: 2440:Orthogonality 2438: 2436: 2433: 2431: 2428: 2427: 2423: 2421: 2419: 2415: 2396: 2393: 2390: 2381: 2375: 2366: 2360: 2354: 2348: 2339: 2335: 2330: 2322: 2319: 2316: 2304: 2303: 2302: 2285: 2282: 2273: 2267: 2261: 2255: 2246: 2242: 2236: 2233: 2230: 2220: 2219: 2218: 2217: 2216:bilinear form 2188: 2185: 2152: 2149: 2138:Bilinear form 2137: 2118: 2115: 2108: 2102: 2093: 2087: 2084: 2077: 2071: 2064: 2058: 2049: 2038: 2037: 2036: 2035: 2016: 2013: 2004: 1998: 1989: 1961: 1952: 1951: 1950: 1949: 1921: 1905: 1902: 1899: 1890: 1884: 1879: 1875: 1867: 1866: 1865: 1864: 1860: 1856: 1852: 1828: 1820: 1818: 1804: 1801: 1794: 1788: 1780: 1764: 1741: 1738: 1731: 1725: 1719: 1713: 1704: 1696: 1695: 1694: 1693: 1674: 1671: 1662: 1656: 1647: 1639: 1638: 1637: 1636: 1633: 1629: 1625: 1598: 1595: 1583: 1581: 1579: 1560: 1554: 1546: 1543: 1525: 1509: 1506: 1498: 1482: 1479: 1456: 1453: 1450: 1440: 1402: 1388: 1384: 1361: 1345: 1342: 1335: 1329: 1321: 1313: 1311: 1294: 1263: 1255: 1251: 1245: 1240: 1237: 1234: 1230: 1222: 1210: 1206: 1200: 1195: 1192: 1189: 1185: 1174: 1173: 1172: 1171: 1167: 1147: 1137: 1134: 1131: 1126: 1110: 1092: 1088: 1084: 1081: 1078: 1073: 1069: 1060: 1057:objects on a 1044: 1036: 1032: 1024: 1022: 1020: 1016: 1012: 1008: 1005:in which the 1004: 999: 997: 996:probabilities 993: 988: 971: 967: 957: 937: 933: 927: 923: 918: 914: 911: 906: 902: 875: 870: 866: 860: 856: 853: 848: 844: 820: 815: 811: 803: 785: 781: 760: 752: 748: 740: 738: 736: 717: 708: 702: 697: 694: 691: 687: 678: 672: 666: 660: 655: 652: 649: 645: 634: 633: 632: 631: 627: 626:weighted mean 605: 599: 594: 591: 588: 584: 572: 563: 554: 553: 552: 551: 547: 543: 539: 520: 514: 508: 503: 500: 497: 493: 485: 484: 483: 482: 478: 474: 470: 466: 462: 458: 453: 451: 432: 426: 420: 414: 408: 403: 400: 397: 393: 385: 384: 383: 381: 377: 359: 346: 343: 340: 333: 314: 308: 302: 297: 294: 291: 287: 279: 278: 277: 275: 262: 242: 234: 228: 224: 200: 197: 194: 185: 183: 167: 164: 158: 152: 144: 140: 124: 117: 114: 96: 83: 80: 77: 65: 60: 58: 56: 52: 48: 44: 40: 35: 27: 19: 2518: 2512: 2495: 2489: 2411: 2300: 2141: 2033: 2031: 1925: 1862: 1858: 1854: 1826: 1824: 1756: 1691: 1689: 1631: 1587: 1437:could be an 1317: 1278: 1033:arises from 1030: 1028: 1000: 989: 744: 734: 732: 623: 537: 535: 480: 476: 472: 464: 456: 454: 447: 376:weighted sum 375: 331: 330:but given a 329: 230: 186: 181: 69: 39:weighted sum 38: 33: 31: 26: 18:Weighted sum 1849:, then the 1630:, then the 1003:regressions 469:cardinality 231:unweighted 229:, then the 2541:Categories 2481:References 1632:unweighted 1542:measurable 747:statistics 741:Statistics 463:subset of 182:unweighted 47:statistics 2470:Weighting 2344:Ω 2340:∫ 2326:⟩ 2314:⟨ 2251:Ω 2247:∫ 2240:⟩ 2228:⟨ 2195:→ 2192:Ω 2189:: 2159:→ 2156:Ω 2153:: 2098:Ω 2094:∫ 2054:Ω 2050:∫ 1994:Ω 1990:∫ 1980:Ω 1934:Ω 1876:∫ 1837:Ω 1709:Ω 1705:∫ 1652:Ω 1648:∫ 1605:→ 1602:Ω 1599:: 1516:→ 1513:Ω 1510:: 1425:Ω 1369:Ω 1231:∑ 1186:∑ 1135:… 1082:… 1035:mechanics 1025:Mechanics 924:∑ 903:σ 867:σ 812:σ 695:∈ 688:∑ 653:∈ 646:∑ 592:∈ 585:∑ 501:∈ 494:∑ 401:∈ 394:∑ 350:→ 344:: 295:∈ 288:∑ 204:→ 198:: 143:countable 87:→ 81:: 2424:See also 1635:integral 1628:function 1626:-valued 1545:function 1472:. Here 1439:interval 1358:on some 1322:such as 802:variance 735:relative 227:function 225:-valued 113:discrete 51:analysis 2530:, 1981. 2507:, 1980. 2032:by the 1948:average 1578:density 1320:measure 1166:fulcrum 1107:(where 624:by the 550:average 479:by the 55:measure 2526:  2503:  2388:  2373:  2280:  2011:  1897:  1851:volume 1777:to be 1669:  1383:subset 1360:domain 1109:weight 542:finite 461:finite 374:, the 139:finite 1857:) of 1622:is a 1385:of a 1059:lever 800:with 540:is a 475:| of 459:is a 221:is a 2524:ISBN 2501:ISBN 2178:and 1853:vol( 1624:real 1499:and 1013:, a 990:The 954:The 751:bias 546:mean 223:real 49:and 2142:If 1926:If 1825:If 1588:If 1495:is 1001:In 628:or 548:or 536:If 455:If 378:or 255:on 235:of 233:sum 141:or 116:set 41:or 2543:: 2522:, 2499:, 2420:. 2336::= 2243::= 1580:. 452:. 165::= 32:A 2397:. 2394:x 2391:d 2385:) 2382:x 2379:( 2376:w 2370:) 2367:x 2364:( 2361:g 2358:) 2355:x 2352:( 2349:f 2331:w 2323:g 2320:, 2317:f 2286:x 2283:d 2277:) 2274:x 2271:( 2268:g 2265:) 2262:x 2259:( 2256:f 2237:g 2234:, 2231:f 2200:R 2186:g 2164:R 2150:f 2119:x 2116:d 2112:) 2109:x 2106:( 2103:w 2088:x 2085:d 2081:) 2078:x 2075:( 2072:w 2068:) 2065:x 2062:( 2059:f 2017:x 2014:d 2008:) 2005:x 2002:( 1999:f 1983:) 1977:( 1973:l 1970:o 1967:v 1962:1 1906:, 1903:x 1900:d 1894:) 1891:x 1888:( 1885:w 1880:E 1859:E 1855:E 1827:E 1805:x 1802:d 1798:) 1795:x 1792:( 1789:w 1765:f 1742:x 1739:d 1735:) 1732:x 1729:( 1726:w 1723:) 1720:x 1717:( 1714:f 1675:x 1672:d 1666:) 1663:x 1660:( 1657:f 1609:R 1596:f 1564:) 1561:x 1558:( 1555:w 1526:+ 1521:R 1507:w 1483:x 1480:d 1460:] 1457:b 1454:, 1451:a 1448:[ 1403:n 1398:R 1346:x 1343:d 1339:) 1336:x 1333:( 1330:w 1309:. 1295:i 1290:x 1264:, 1256:i 1252:w 1246:n 1241:1 1238:= 1235:i 1223:i 1218:x 1211:i 1207:w 1201:n 1196:1 1193:= 1190:i 1162:, 1148:n 1143:x 1138:, 1132:, 1127:1 1122:x 1093:n 1089:w 1085:, 1079:, 1074:1 1070:w 1045:n 986:. 972:i 968:w 952:. 938:i 934:w 928:i 919:/ 915:1 912:= 907:2 891:, 876:2 871:i 861:/ 857:1 854:= 849:i 845:w 821:2 816:i 786:i 782:f 761:f 718:. 712:) 709:a 706:( 703:w 698:A 692:a 682:) 679:a 676:( 673:w 670:) 667:a 664:( 661:f 656:A 650:a 609:) 606:a 603:( 600:f 595:A 589:a 577:| 573:A 569:| 564:1 538:A 521:. 518:) 515:a 512:( 509:w 504:B 498:a 477:B 473:B 471:| 465:A 457:B 433:. 430:) 427:a 424:( 421:w 418:) 415:a 412:( 409:f 404:A 398:a 360:+ 355:R 347:A 341:w 315:; 312:) 309:a 306:( 303:f 298:A 292:a 263:A 243:f 208:R 201:A 195:f 168:1 162:) 159:a 156:( 153:w 125:A 97:+ 92:R 84:A 78:w 20:)

Index

Weighted sum
weighted average
statistics
analysis
measure
discrete
set
finite
countable
real
function
sum
conical combination
numerical integration
finite
cardinality
finite
mean
average
weighted mean
weighted average
statistics
bias
variance
maximum likelihood
expected value
probabilities
regressions
dependent variable
independent variable

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