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Type 'q()' to quit R. > x <- array(list(1687 + ,0 + ,-183.923544 + ,1508 + ,0 + ,-177.0726091 + ,1507 + ,0 + ,-228.6351091 + ,1385 + ,0 + ,-237.4476091 + ,1632 + ,0 + ,-127.7601091 + ,1511 + ,0 + ,-193.0101091 + ,1559 + ,0 + ,-220.6351091 + ,1630 + ,0 + ,-164.5101091 + ,1579 + ,0 + ,-268.3226091 + ,1653 + ,0 + ,-333.6976091 + ,2152 + ,0 + ,-34.26010911 + ,2148 + ,0 + ,-154.8851091 + ,1752 + ,0 + ,-97.74528053 + ,1765 + ,0 + ,101.1056549 + ,1717 + ,0 + ,2.543154874 + ,1558 + ,0 + ,-43.26934513 + ,1575 + ,0 + ,-163.5818451 + ,1520 + ,0 + ,-162.8318451 + ,1805 + ,0 + ,46.54315487 + ,1800 + ,0 + ,26.66815487 + ,1719 + ,0 + ,-107.1443451 + ,2008 + ,0 + ,42.48065487 + ,2242 + ,0 + ,76.91815487 + ,2478 + ,0 + ,196.2931549 + ,2030 + ,0 + ,201.4329835 + ,1655 + ,0 + ,12.28391886 + ,1693 + ,0 + ,-0.278581137 + ,1623 + ,0 + ,42.90891886 + ,1805 + ,0 + ,87.59641886 + ,1746 + ,0 + ,84.34641886 + ,1795 + ,0 + ,57.72141886 + ,1926 + ,0 + ,173.8464189 + ,1619 + ,0 + ,-185.9660811 + ,1992 + ,0 + ,47.65891886 + ,2233 + ,0 + ,89.09641886 + ,2192 + ,0 + ,-68.52858114 + ,2080 + ,0 + ,272.6112475 + ,1768 + ,0 + ,146.4621829 + ,1835 + ,0 + ,162.8996829 + ,1569 + ,0 + ,10.08718285 + ,1976 + ,0 + ,279.7746829 + ,1853 + ,0 + ,212.5246829 + ,1965 + ,0 + ,248.8996829 + ,1689 + ,0 + ,-41.97531715 + ,1778 + ,0 + ,-5.787817149 + ,1976 + ,0 + ,52.83718285 + ,2397 + ,0 + ,274.2746829 + ,2654 + ,0 + ,414.6496829 + ,2097 + ,0 + ,310.7895114 + ,1963 + ,0 + ,362.6404468 + ,1677 + ,0 + ,26.07794684 + ,1941 + ,0 + ,403.2654468 + ,2003 + ,0 + ,327.9529468 + ,1813 + ,0 + ,193.7029468 + ,2012 + ,0 + ,317.0779468 + ,1912 + ,0 + ,202.2029468 + ,2084 + ,0 + ,321.3904468 + ,2080 + ,0 + ,178.0154468 + ,2118 + ,0 + ,16.45294684 + ,2150 + ,0 + ,-68.17205316 + ,1608 + ,0 + ,-157.0322246 + ,1503 + ,0 + ,-76.18128917 + ,1548 + ,0 + ,-81.74378917 + ,1382 + ,0 + ,-134.5562892 + ,1731 + ,0 + ,77.13121083 + ,1798 + ,0 + ,199.8812108 + ,1779 + ,0 + ,105.2562108 + ,1887 + ,0 + ,198.3812108 + ,2004 + ,0 + ,262.5687108 + ,2077 + ,0 + ,196.1937108 + ,2092 + ,0 + ,11.63121083 + ,2051 + ,0 + ,-145.9937892 + ,1577 + ,0 + ,-166.8539606 + ,1356 + ,0 + ,-202.0030252 + ,1652 + ,0 + ,43.43447482 + ,1382 + ,0 + ,-113.3780252 + ,1519 + ,0 + ,-113.6905252 + ,1421 + ,0 + ,-155.9405252 + ,1442 + ,0 + ,-210.5655252 + ,1543 + ,0 + ,-124.4405252 + ,1656 + ,0 + ,-64.25302518 + ,1561 + ,0 + ,-298.6280252 + ,1905 + ,0 + ,-154.1905252 + ,2199 + ,0 + ,23.18447482 + ,1473 + ,0 + ,-249.6756966 + ,1655 + ,0 + ,118.1752388 + ,1407 + ,0 + ,-180.3872612 + ,1395 + ,0 + ,-79.19976119 + ,1530 + ,0 + ,-81.51226119 + ,1309 + ,0 + ,-246.7622612 + ,1526 + ,0 + ,-105.3872612 + ,1327 + ,0 + ,-319.2622612 + ,1627 + ,0 + ,-72.07476119 + ,1748 + ,0 + ,-90.44976119 + ,1958 + ,0 + ,-80.01226119 + ,2274 + ,0 + ,119.3627388 + ,1648 + ,0 + ,-53.49743261 + ,1401 + ,0 + ,-114.6464972 + ,1411 + ,0 + ,-155.2089972 + ,1403 + ,0 + ,-50.02149721 + ,1394 + ,0 + ,-196.3339972 + ,1520 + ,0 + ,-14.58399721 + ,1528 + ,0 + ,-82.20899721 + ,1643 + ,0 + ,17.91600279 + ,1515 + ,0 + ,-162.8964972 + ,1685 + ,0 + ,-132.2714972 + ,2000 + ,0 + ,-16.83399721 + ,2215 + ,0 + ,81.54100279 + ,1956 + ,0 + ,275.6808314 + ,1462 + ,0 + ,-32.46823322 + ,1563 + ,0 + ,17.96926678 + ,1459 + ,0 + ,27.15676678 + ,1446 + ,0 + ,-123.1557332 + ,1622 + ,0 + ,108.5942668 + ,1657 + ,0 + ,67.96926678 + ,1638 + ,0 + ,34.09426678 + ,1643 + ,0 + ,-13.71823322 + ,1683 + ,0 + ,-113.0932332 + ,2050 + ,0 + ,54.34426678 + ,2262 + ,0 + ,149.7192668 + ,1813 + ,0 + ,153.8590954 + ,1445 + ,0 + ,-28.28996923 + ,1762 + ,0 + ,238.1475308 + ,1461 + ,0 + ,50.33503077 + ,1556 + ,0 + ,8.022530771 + ,1431 + ,0 + ,-61.22746923 + ,1427 + ,0 + ,-140.8524692 + ,1554 + ,0 + ,-28.72746923 + ,1645 + ,0 + ,9.460030771 + ,1653 + ,0 + ,-121.9149692 + ,2016 + ,0 + ,41.52253077 + ,2207 + ,0 + ,115.8975308 + ,1665 + ,0 + ,27.03735936 + ,1361 + ,0 + ,-91.11170524 + ,1506 + ,0 + ,3.325794759 + ,1360 + ,0 + ,-29.48670524 + ,1453 + ,0 + ,-73.79920524 + ,1522 + ,0 + ,50.95079476 + ,1460 + ,0 + ,-86.67420524 + ,1552 + ,0 + ,-9.54920524 + ,1548 + ,0 + ,-66.36170524 + ,1827 + ,0 + ,73.26329476 + ,1737 + ,0 + ,-216.2992052 + ,1941 + ,0 + ,-128.9242052 + ,1474 + ,0 + ,-142.7843767 + ,1458 + ,0 + ,27.06655875 + ,1542 + ,0 + ,60.50405875 + ,1404 + ,0 + ,35.69155875 + ,1522 + ,0 + ,16.37905875 + ,1385 + ,0 + ,-64.87094125 + ,1641 + ,0 + ,115.5040587 + ,1510 + ,0 + ,-30.37094125 + ,1681 + ,0 + ,87.81655875 + ,1938 + ,0 + ,205.4415587 + ,1868 + ,0 + ,-64.12094125 + ,1726 + ,0 + ,-322.7459413 + ,1456 + ,0 + ,-139.6061127 + ,1445 + ,0 + ,35.24482274 + ,1456 + ,0 + ,-4.317677263 + ,1365 + ,0 + ,17.86982274 + ,1487 + ,0 + ,2.557322737 + ,1558 + ,0 + ,129.3073227 + ,1488 + ,0 + ,-16.31767726 + ,1684 + ,0 + ,164.8073227 + ,1594 + ,0 + ,21.99482274 + ,1850 + ,0 + ,138.6198227 + ,1998 + ,0 + ,87.05732274 + ,2079 + ,0 + ,51.43232274 + ,1494 + ,0 + ,-80.42784867 + ,1057 + ,1 + ,-105.1918797 + ,1218 + ,1 + ,5.245620328 + ,1168 + ,1 + ,68.43312033 + ,1236 + ,1 + ,-0.879379672 + ,1076 + ,1 + ,-105.1293797 + ,1174 + ,1 + ,-82.75437967 + ,1139 + ,1 + ,-132.6293797 + ,1427 + ,1 + ,102.5581203 + ,1487 + ,1 + ,23.18312033 + ,1483 + ,1 + ,-180.3793797 + ,1513 + ,1 + ,-267.0043797 + ,1357 + ,1 + ,30.13544892 + ,1165 + ,1 + ,23.98638432 + ,1282 + ,1 + ,90.42388432 + ,1110 + ,1 + ,31.61138432 + ,1297 + ,1 + ,81.29888432 + ,1185 + ,1 + ,25.04888432 + ,1222 + ,1 + ,-13.57611568 + ,1284 + ,1 + ,33.54888432 + ,1444 + ,1 + ,140.7363843 + ,1575 + ,1 + ,132.3613843 + ,1737 + ,1 + ,94.79888432 + ,1763 + ,1 + ,4.173884316) + ,dim=c(3 + ,192) + ,dimnames=list(c('Y' + ,'X' + ,'T') + ,1:192)) > y <- array(NA,dim=c(3,192),dimnames=list(c('Y','X','T'),1:192)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = '' > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > ylab = '' > xlab = '' > main = '' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Y X T M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 1687 0 -183.9235440 1 0 0 0 0 0 0 0 0 0 0 1 2 1508 0 -177.0726091 0 1 0 0 0 0 0 0 0 0 0 2 3 1507 0 -228.6351091 0 0 1 0 0 0 0 0 0 0 0 3 4 1385 0 -237.4476091 0 0 0 1 0 0 0 0 0 0 0 4 5 1632 0 -127.7601091 0 0 0 0 1 0 0 0 0 0 0 5 6 1511 0 -193.0101091 0 0 0 0 0 1 0 0 0 0 0 6 7 1559 0 -220.6351091 0 0 0 0 0 0 1 0 0 0 0 7 8 1630 0 -164.5101091 0 0 0 0 0 0 0 1 0 0 0 8 9 1579 0 -268.3226091 0 0 0 0 0 0 0 0 1 0 0 9 10 1653 0 -333.6976091 0 0 0 0 0 0 0 0 0 1 0 10 11 2152 0 -34.2601091 0 0 0 0 0 0 0 0 0 0 1 11 12 2148 0 -154.8851091 0 0 0 0 0 0 0 0 0 0 0 12 13 1752 0 -97.7452805 1 0 0 0 0 0 0 0 0 0 0 13 14 1765 0 101.1056549 0 1 0 0 0 0 0 0 0 0 0 14 15 1717 0 2.5431549 0 0 1 0 0 0 0 0 0 0 0 15 16 1558 0 -43.2693451 0 0 0 1 0 0 0 0 0 0 0 16 17 1575 0 -163.5818451 0 0 0 0 1 0 0 0 0 0 0 17 18 1520 0 -162.8318451 0 0 0 0 0 1 0 0 0 0 0 18 19 1805 0 46.5431549 0 0 0 0 0 0 1 0 0 0 0 19 20 1800 0 26.6681549 0 0 0 0 0 0 0 1 0 0 0 20 21 1719 0 -107.1443451 0 0 0 0 0 0 0 0 1 0 0 21 22 2008 0 42.4806549 0 0 0 0 0 0 0 0 0 1 0 22 23 2242 0 76.9181549 0 0 0 0 0 0 0 0 0 0 1 23 24 2478 0 196.2931549 0 0 0 0 0 0 0 0 0 0 0 24 25 2030 0 201.4329835 1 0 0 0 0 0 0 0 0 0 0 25 26 1655 0 12.2839189 0 1 0 0 0 0 0 0 0 0 0 26 27 1693 0 -0.2785811 0 0 1 0 0 0 0 0 0 0 0 27 28 1623 0 42.9089189 0 0 0 1 0 0 0 0 0 0 0 28 29 1805 0 87.5964189 0 0 0 0 1 0 0 0 0 0 0 29 30 1746 0 84.3464189 0 0 0 0 0 1 0 0 0 0 0 30 31 1795 0 57.7214189 0 0 0 0 0 0 1 0 0 0 0 31 32 1926 0 173.8464189 0 0 0 0 0 0 0 1 0 0 0 32 33 1619 0 -185.9660811 0 0 0 0 0 0 0 0 1 0 0 33 34 1992 0 47.6589189 0 0 0 0 0 0 0 0 0 1 0 34 35 2233 0 89.0964189 0 0 0 0 0 0 0 0 0 0 1 35 36 2192 0 -68.5285811 0 0 0 0 0 0 0 0 0 0 0 36 37 2080 0 272.6112475 1 0 0 0 0 0 0 0 0 0 0 37 38 1768 0 146.4621829 0 1 0 0 0 0 0 0 0 0 0 38 39 1835 0 162.8996829 0 0 1 0 0 0 0 0 0 0 0 39 40 1569 0 10.0871828 0 0 0 1 0 0 0 0 0 0 0 40 41 1976 0 279.7746829 0 0 0 0 1 0 0 0 0 0 0 41 42 1853 0 212.5246829 0 0 0 0 0 1 0 0 0 0 0 42 43 1965 0 248.8996829 0 0 0 0 0 0 1 0 0 0 0 43 44 1689 0 -41.9753172 0 0 0 0 0 0 0 1 0 0 0 44 45 1778 0 -5.7878171 0 0 0 0 0 0 0 0 1 0 0 45 46 1976 0 52.8371828 0 0 0 0 0 0 0 0 0 1 0 46 47 2397 0 274.2746829 0 0 0 0 0 0 0 0 0 0 1 47 48 2654 0 414.6496829 0 0 0 0 0 0 0 0 0 0 0 48 49 2097 0 310.7895114 1 0 0 0 0 0 0 0 0 0 0 49 50 1963 0 362.6404468 0 1 0 0 0 0 0 0 0 0 0 50 51 1677 0 26.0779468 0 0 1 0 0 0 0 0 0 0 0 51 52 1941 0 403.2654468 0 0 0 1 0 0 0 0 0 0 0 52 53 2003 0 327.9529468 0 0 0 0 1 0 0 0 0 0 0 53 54 1813 0 193.7029468 0 0 0 0 0 1 0 0 0 0 0 54 55 2012 0 317.0779468 0 0 0 0 0 0 1 0 0 0 0 55 56 1912 0 202.2029468 0 0 0 0 0 0 0 1 0 0 0 56 57 2084 0 321.3904468 0 0 0 0 0 0 0 0 1 0 0 57 58 2080 0 178.0154468 0 0 0 0 0 0 0 0 0 1 0 58 59 2118 0 16.4529468 0 0 0 0 0 0 0 0 0 0 1 59 60 2150 0 -68.1720532 0 0 0 0 0 0 0 0 0 0 0 60 61 1608 0 -157.0322246 1 0 0 0 0 0 0 0 0 0 0 61 62 1503 0 -76.1812892 0 1 0 0 0 0 0 0 0 0 0 62 63 1548 0 -81.7437892 0 0 1 0 0 0 0 0 0 0 0 63 64 1382 0 -134.5562892 0 0 0 1 0 0 0 0 0 0 0 64 65 1731 0 77.1312108 0 0 0 0 1 0 0 0 0 0 0 65 66 1798 0 199.8812108 0 0 0 0 0 1 0 0 0 0 0 66 67 1779 0 105.2562108 0 0 0 0 0 0 1 0 0 0 0 67 68 1887 0 198.3812108 0 0 0 0 0 0 0 1 0 0 0 68 69 2004 0 262.5687108 0 0 0 0 0 0 0 0 1 0 0 69 70 2077 0 196.1937108 0 0 0 0 0 0 0 0 0 1 0 70 71 2092 0 11.6312108 0 0 0 0 0 0 0 0 0 0 1 71 72 2051 0 -145.9937892 0 0 0 0 0 0 0 0 0 0 0 72 73 1577 0 -166.8539606 1 0 0 0 0 0 0 0 0 0 0 73 74 1356 0 -202.0030252 0 1 0 0 0 0 0 0 0 0 0 74 75 1652 0 43.4344748 0 0 1 0 0 0 0 0 0 0 0 75 76 1382 0 -113.3780252 0 0 0 1 0 0 0 0 0 0 0 76 77 1519 0 -113.6905252 0 0 0 0 1 0 0 0 0 0 0 77 78 1421 0 -155.9405252 0 0 0 0 0 1 0 0 0 0 0 78 79 1442 0 -210.5655252 0 0 0 0 0 0 1 0 0 0 0 79 80 1543 0 -124.4405252 0 0 0 0 0 0 0 1 0 0 0 80 81 1656 0 -64.2530252 0 0 0 0 0 0 0 0 1 0 0 81 82 1561 0 -298.6280252 0 0 0 0 0 0 0 0 0 1 0 82 83 1905 0 -154.1905252 0 0 0 0 0 0 0 0 0 0 1 83 84 2199 0 23.1844748 0 0 0 0 0 0 0 0 0 0 0 84 85 1473 0 -249.6756966 1 0 0 0 0 0 0 0 0 0 0 85 86 1655 0 118.1752388 0 1 0 0 0 0 0 0 0 0 0 86 87 1407 0 -180.3872612 0 0 1 0 0 0 0 0 0 0 0 87 88 1395 0 -79.1997612 0 0 0 1 0 0 0 0 0 0 0 88 89 1530 0 -81.5122612 0 0 0 0 1 0 0 0 0 0 0 89 90 1309 0 -246.7622612 0 0 0 0 0 1 0 0 0 0 0 90 91 1526 0 -105.3872612 0 0 0 0 0 0 1 0 0 0 0 91 92 1327 0 -319.2622612 0 0 0 0 0 0 0 1 0 0 0 92 93 1627 0 -72.0747612 0 0 0 0 0 0 0 0 1 0 0 93 94 1748 0 -90.4497612 0 0 0 0 0 0 0 0 0 1 0 94 95 1958 0 -80.0122612 0 0 0 0 0 0 0 0 0 0 1 95 96 2274 0 119.3627388 0 0 0 0 0 0 0 0 0 0 0 96 97 1648 0 -53.4974326 1 0 0 0 0 0 0 0 0 0 0 97 98 1401 0 -114.6464972 0 1 0 0 0 0 0 0 0 0 0 98 99 1411 0 -155.2089972 0 0 1 0 0 0 0 0 0 0 0 99 100 1403 0 -50.0214972 0 0 0 1 0 0 0 0 0 0 0 100 101 1394 0 -196.3339972 0 0 0 0 1 0 0 0 0 0 0 101 102 1520 0 -14.5839972 0 0 0 0 0 1 0 0 0 0 0 102 103 1528 0 -82.2089972 0 0 0 0 0 0 1 0 0 0 0 103 104 1643 0 17.9160028 0 0 0 0 0 0 0 1 0 0 0 104 105 1515 0 -162.8964972 0 0 0 0 0 0 0 0 1 0 0 105 106 1685 0 -132.2714972 0 0 0 0 0 0 0 0 0 1 0 106 107 2000 0 -16.8339972 0 0 0 0 0 0 0 0 0 0 1 107 108 2215 0 81.5410028 0 0 0 0 0 0 0 0 0 0 0 108 109 1956 0 275.6808314 1 0 0 0 0 0 0 0 0 0 0 109 110 1462 0 -32.4682332 0 1 0 0 0 0 0 0 0 0 0 110 111 1563 0 17.9692668 0 0 1 0 0 0 0 0 0 0 0 111 112 1459 0 27.1567668 0 0 0 1 0 0 0 0 0 0 0 112 113 1446 0 -123.1557332 0 0 0 0 1 0 0 0 0 0 0 113 114 1622 0 108.5942668 0 0 0 0 0 1 0 0 0 0 0 114 115 1657 0 67.9692668 0 0 0 0 0 0 1 0 0 0 0 115 116 1638 0 34.0942668 0 0 0 0 0 0 0 1 0 0 0 116 117 1643 0 -13.7182332 0 0 0 0 0 0 0 0 1 0 0 117 118 1683 0 -113.0932332 0 0 0 0 0 0 0 0 0 1 0 118 119 2050 0 54.3442668 0 0 0 0 0 0 0 0 0 0 1 119 120 2262 0 149.7192668 0 0 0 0 0 0 0 0 0 0 0 120 121 1813 0 153.8590954 1 0 0 0 0 0 0 0 0 0 0 121 122 1445 0 -28.2899692 0 1 0 0 0 0 0 0 0 0 0 122 123 1762 0 238.1475308 0 0 1 0 0 0 0 0 0 0 0 123 124 1461 0 50.3350308 0 0 0 1 0 0 0 0 0 0 0 124 125 1556 0 8.0225308 0 0 0 0 1 0 0 0 0 0 0 125 126 1431 0 -61.2274692 0 0 0 0 0 1 0 0 0 0 0 126 127 1427 0 -140.8524692 0 0 0 0 0 0 1 0 0 0 0 127 128 1554 0 -28.7274692 0 0 0 0 0 0 0 1 0 0 0 128 129 1645 0 9.4600308 0 0 0 0 0 0 0 0 1 0 0 129 130 1653 0 -121.9149692 0 0 0 0 0 0 0 0 0 1 0 130 131 2016 0 41.5225308 0 0 0 0 0 0 0 0 0 0 1 131 132 2207 0 115.8975308 0 0 0 0 0 0 0 0 0 0 0 132 133 1665 0 27.0373594 1 0 0 0 0 0 0 0 0 0 0 133 134 1361 0 -91.1117052 0 1 0 0 0 0 0 0 0 0 0 134 135 1506 0 3.3257948 0 0 1 0 0 0 0 0 0 0 0 135 136 1360 0 -29.4867052 0 0 0 1 0 0 0 0 0 0 0 136 137 1453 0 -73.7992052 0 0 0 0 1 0 0 0 0 0 0 137 138 1522 0 50.9507948 0 0 0 0 0 1 0 0 0 0 0 138 139 1460 0 -86.6742052 0 0 0 0 0 0 1 0 0 0 0 139 140 1552 0 -9.5492052 0 0 0 0 0 0 0 1 0 0 0 140 141 1548 0 -66.3617052 0 0 0 0 0 0 0 0 1 0 0 141 142 1827 0 73.2632948 0 0 0 0 0 0 0 0 0 1 0 142 143 1737 0 -216.2992052 0 0 0 0 0 0 0 0 0 0 1 143 144 1941 0 -128.9242052 0 0 0 0 0 0 0 0 0 0 0 144 145 1474 0 -142.7843767 1 0 0 0 0 0 0 0 0 0 0 145 146 1458 0 27.0665587 0 1 0 0 0 0 0 0 0 0 0 146 147 1542 0 60.5040587 0 0 1 0 0 0 0 0 0 0 0 147 148 1404 0 35.6915587 0 0 0 1 0 0 0 0 0 0 0 148 149 1522 0 16.3790587 0 0 0 0 1 0 0 0 0 0 0 149 150 1385 0 -64.8709413 0 0 0 0 0 1 0 0 0 0 0 150 151 1641 0 115.5040587 0 0 0 0 0 0 1 0 0 0 0 151 152 1510 0 -30.3709413 0 0 0 0 0 0 0 1 0 0 0 152 153 1681 0 87.8165587 0 0 0 0 0 0 0 0 1 0 0 153 154 1938 0 205.4415587 0 0 0 0 0 0 0 0 0 1 0 154 155 1868 0 -64.1209413 0 0 0 0 0 0 0 0 0 0 1 155 156 1726 0 -322.7459413 0 0 0 0 0 0 0 0 0 0 0 156 157 1456 0 -139.6061127 1 0 0 0 0 0 0 0 0 0 0 157 158 1445 0 35.2448227 0 1 0 0 0 0 0 0 0 0 0 158 159 1456 0 -4.3176773 0 0 1 0 0 0 0 0 0 0 0 159 160 1365 0 17.8698227 0 0 0 1 0 0 0 0 0 0 0 160 161 1487 0 2.5573227 0 0 0 0 1 0 0 0 0 0 0 161 162 1558 0 129.3073227 0 0 0 0 0 1 0 0 0 0 0 162 163 1488 0 -16.3176773 0 0 0 0 0 0 1 0 0 0 0 163 164 1684 0 164.8073227 0 0 0 0 0 0 0 1 0 0 0 164 165 1594 0 21.9948227 0 0 0 0 0 0 0 0 1 0 0 165 166 1850 0 138.6198227 0 0 0 0 0 0 0 0 0 1 0 166 167 1998 0 87.0573227 0 0 0 0 0 0 0 0 0 0 1 167 168 2079 0 51.4323227 0 0 0 0 0 0 0 0 0 0 0 168 169 1494 0 -80.4278487 1 0 0 0 0 0 0 0 0 0 0 169 170 1057 1 -105.1918797 0 1 0 0 0 0 0 0 0 0 0 170 171 1218 1 5.2456203 0 0 1 0 0 0 0 0 0 0 0 171 172 1168 1 68.4331203 0 0 0 1 0 0 0 0 0 0 0 172 173 1236 1 -0.8793797 0 0 0 0 1 0 0 0 0 0 0 173 174 1076 1 -105.1293797 0 0 0 0 0 1 0 0 0 0 0 174 175 1174 1 -82.7543797 0 0 0 0 0 0 1 0 0 0 0 175 176 1139 1 -132.6293797 0 0 0 0 0 0 0 1 0 0 0 176 177 1427 1 102.5581203 0 0 0 0 0 0 0 0 1 0 0 177 178 1487 1 23.1831203 0 0 0 0 0 0 0 0 0 1 0 178 179 1483 1 -180.3793797 0 0 0 0 0 0 0 0 0 0 1 179 180 1513 1 -267.0043797 0 0 0 0 0 0 0 0 0 0 0 180 181 1357 1 30.1354489 1 0 0 0 0 0 0 0 0 0 0 181 182 1165 1 23.9863843 0 1 0 0 0 0 0 0 0 0 0 182 183 1282 1 90.4238843 0 0 1 0 0 0 0 0 0 0 0 183 184 1110 1 31.6113843 0 0 0 1 0 0 0 0 0 0 0 184 185 1297 1 81.2988843 0 0 0 0 1 0 0 0 0 0 0 185 186 1185 1 25.0488843 0 0 0 0 0 1 0 0 0 0 0 186 187 1222 1 -13.5761157 0 0 0 0 0 0 1 0 0 0 0 187 188 1284 1 33.5488843 0 0 0 0 0 0 0 1 0 0 0 188 189 1444 1 140.7363843 0 0 0 0 0 0 0 0 1 0 0 189 190 1575 1 132.3613843 0 0 0 0 0 0 0 0 0 1 0 190 191 1737 1 94.7988843 0 0 0 0 0 0 0 0 0 0 1 191 192 1763 1 4.1738843 0 0 0 0 0 0 0 0 0 0 0 192 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X T M1 M2 M3 2324.063 -226.385 1.000 -451.375 -635.461 -583.134 M4 M5 M6 M7 M8 M9 -694.556 -555.479 -609.464 -532.074 -515.434 -460.857 M10 M11 t -319.717 -118.390 -1.765 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -4.639e-07 -1.146e-08 1.091e-09 1.549e-08 7.077e-08 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.324e+03 1.210e-08 1.921e+11 <2e-16 *** X -2.264e+02 1.128e-08 -2.007e+10 <2e-16 *** T 1.000e+00 2.060e-11 4.855e+10 <2e-16 *** M1 -4.514e+02 1.482e-08 -3.045e+10 <2e-16 *** M2 -6.355e+02 1.482e-08 -4.287e+10 <2e-16 *** M3 -5.831e+02 1.482e-08 -3.935e+10 <2e-16 *** M4 -6.946e+02 1.482e-08 -4.687e+10 <2e-16 *** M5 -5.555e+02 1.482e-08 -3.749e+10 <2e-16 *** M6 -6.095e+02 1.481e-08 -4.114e+10 <2e-16 *** M7 -5.321e+02 1.481e-08 -3.592e+10 <2e-16 *** M8 -5.154e+02 1.481e-08 -3.480e+10 <2e-16 *** M9 -4.609e+02 1.481e-08 -3.112e+10 <2e-16 *** M10 -3.197e+02 1.481e-08 -2.159e+10 <2e-16 *** M11 -1.184e+02 1.481e-08 -7.995e+09 <2e-16 *** t -1.765e+00 6.610e-11 -2.670e+10 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 4.189e-08 on 177 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 6.523e+20 on 14 and 177 DF, p-value: < 2.2e-16 > postscript(file="/var/www/html/rcomp/tmp/1241x1227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2gncz1227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/38vl51227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4sf071227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5mddd1227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 192 Frequency = 1 1 2 3 4 5 -4.638531e-07 6.451631e-09 1.349050e-08 3.038542e-09 8.661236e-09 6 7 8 9 10 3.120701e-09 3.846301e-09 -1.372984e-09 7.095257e-09 2.435004e-09 11 12 13 14 15 1.521052e-08 9.372542e-09 5.017527e-08 -1.452522e-08 1.974449e-08 16 17 18 19 20 1.425827e-08 -4.088163e-09 -1.135780e-08 1.315455e-08 9.925313e-09 21 22 23 24 25 -1.081754e-08 8.885818e-09 1.860844e-08 -1.352035e-08 -1.355786e-09 26 27 28 29 30 1.411336e-08 1.713027e-08 8.310528e-09 1.563931e-08 8.474500e-09 31 32 33 34 35 9.172209e-09 -3.762135e-08 -2.244070e-08 5.061025e-09 1.460007e-08 36 37 38 39 40 1.973140e-08 -1.691038e-08 -4.309236e-08 -3.783571e-08 5.481514e-09 41 42 43 44 45 -4.308668e-08 -4.857399e-08 -4.952750e-08 4.346043e-09 8.147808e-09 46 47 48 49 50 1.236177e-09 -4.394251e-08 -4.662156e-08 6.839981e-08 3.755246e-08 51 52 53 54 55 1.206110e-08 3.148742e-08 4.196140e-08 3.823016e-08 3.499640e-08 56 57 58 59 60 3.425704e-08 3.688344e-08 3.426611e-08 9.125697e-09 1.234367e-08 61 62 63 64 65 6.697200e-08 5.364594e-09 1.119789e-08 3.189430e-08 4.846221e-09 66 67 68 69 70 2.437896e-08 2.685906e-08 2.066816e-08 2.473609e-08 2.010057e-08 71 72 73 74 75 5.562991e-09 4.069413e-08 5.354022e-08 2.497314e-08 4.227919e-09 76 77 78 79 80 1.765005e-08 2.615838e-08 2.001579e-08 2.144726e-08 1.543992e-08 81 82 83 84 85 -3.873287e-10 1.938050e-08 2.621988e-08 2.570844e-09 4.202183e-08 86 87 88 89 90 2.892279e-09 1.640503e-08 -6.934838e-09 1.625811e-09 8.706914e-09 91 92 93 94 95 5.001545e-09 6.857106e-09 -3.871455e-09 -9.765037e-09 5.864968e-10 96 97 98 99 100 6.360928e-09 3.319089e-08 -4.694758e-09 2.055974e-09 -1.388847e-09 101 102 103 104 105 9.460992e-10 -1.067406e-09 7.048513e-10 -5.669467e-09 -5.180331e-09 106 107 108 109 110 -1.235807e-08 5.241474e-09 3.663050e-09 8.742033e-10 -5.377251e-10 111 112 113 114 115 3.827908e-09 -7.100834e-09 -1.466097e-08 -2.798492e-08 -6.920344e-09 116 117 118 119 120 -9.782501e-09 -2.779208e-09 -2.654976e-08 -3.133271e-10 -2.181285e-08 121 122 123 124 125 -9.622117e-09 -4.336467e-09 -3.563200e-08 -1.139754e-08 -2.788284e-09 126 127 128 129 130 -7.223223e-09 -3.513633e-08 -1.182535e-08 -8.075961e-09 -4.000779e-08 131 132 133 134 135 -3.666283e-09 -3.461573e-08 2.001268e-08 -6.379200e-09 -2.166679e-09 136 137 138 139 140 -1.299459e-08 -3.332877e-09 -1.385259e-08 -1.024563e-08 -1.601711e-08 141 142 143 144 145 -8.778074e-09 -1.881244e-08 -4.059804e-08 -4.188824e-08 7.077447e-08 146 147 148 149 150 -1.316566e-08 -8.354464e-09 -1.839205e-08 -9.385693e-09 -1.450600e-08 151 152 153 154 155 3.076635e-08 -1.916051e-08 -1.650788e-08 2.403404e-08 -8.275833e-09 156 157 158 159 160 4.950264e-08 5.700195e-08 -1.706915e-08 -7.344715e-09 -2.161400e-08 161 162 163 164 165 -9.712485e-09 1.671548e-08 -1.946789e-08 1.203471e-08 -1.847189e-08 166 167 168 169 170 1.209636e-08 -1.592712e-08 -1.399349e-08 1.176180e-08 2.476401e-08 171 172 173 174 175 -4.429559e-10 -1.478693e-08 -2.470116e-09 2.101224e-08 -9.574275e-09 176 177 178 179 180 1.798283e-08 1.756883e-08 -1.672596e-08 2.923449e-08 3.250480e-08 181 182 183 184 185 1.701627e-08 -1.231094e-08 -8.364556e-09 -1.751101e-08 -1.031320e-08 186 187 188 189 190 -1.608881e-08 -1.507655e-08 -2.006185e-08 2.878943e-09 -3.276543e-09 191 192 -1.166695e-08 -4.291769e-09 > postscript(file="/var/www/html/rcomp/tmp/65t271227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 192 Frequency = 1 lag(myerror, k = 1) myerror 0 -4.638531e-07 NA 1 6.451631e-09 -4.638531e-07 2 1.349050e-08 6.451631e-09 3 3.038542e-09 1.349050e-08 4 8.661236e-09 3.038542e-09 5 3.120701e-09 8.661236e-09 6 3.846301e-09 3.120701e-09 7 -1.372984e-09 3.846301e-09 8 7.095257e-09 -1.372984e-09 9 2.435004e-09 7.095257e-09 10 1.521052e-08 2.435004e-09 11 9.372542e-09 1.521052e-08 12 5.017527e-08 9.372542e-09 13 -1.452522e-08 5.017527e-08 14 1.974449e-08 -1.452522e-08 15 1.425827e-08 1.974449e-08 16 -4.088163e-09 1.425827e-08 17 -1.135780e-08 -4.088163e-09 18 1.315455e-08 -1.135780e-08 19 9.925313e-09 1.315455e-08 20 -1.081754e-08 9.925313e-09 21 8.885818e-09 -1.081754e-08 22 1.860844e-08 8.885818e-09 23 -1.352035e-08 1.860844e-08 24 -1.355786e-09 -1.352035e-08 25 1.411336e-08 -1.355786e-09 26 1.713027e-08 1.411336e-08 27 8.310528e-09 1.713027e-08 28 1.563931e-08 8.310528e-09 29 8.474500e-09 1.563931e-08 30 9.172209e-09 8.474500e-09 31 -3.762135e-08 9.172209e-09 32 -2.244070e-08 -3.762135e-08 33 5.061025e-09 -2.244070e-08 34 1.460007e-08 5.061025e-09 35 1.973140e-08 1.460007e-08 36 -1.691038e-08 1.973140e-08 37 -4.309236e-08 -1.691038e-08 38 -3.783571e-08 -4.309236e-08 39 5.481514e-09 -3.783571e-08 40 -4.308668e-08 5.481514e-09 41 -4.857399e-08 -4.308668e-08 42 -4.952750e-08 -4.857399e-08 43 4.346043e-09 -4.952750e-08 44 8.147808e-09 4.346043e-09 45 1.236177e-09 8.147808e-09 46 -4.394251e-08 1.236177e-09 47 -4.662156e-08 -4.394251e-08 48 6.839981e-08 -4.662156e-08 49 3.755246e-08 6.839981e-08 50 1.206110e-08 3.755246e-08 51 3.148742e-08 1.206110e-08 52 4.196140e-08 3.148742e-08 53 3.823016e-08 4.196140e-08 54 3.499640e-08 3.823016e-08 55 3.425704e-08 3.499640e-08 56 3.688344e-08 3.425704e-08 57 3.426611e-08 3.688344e-08 58 9.125697e-09 3.426611e-08 59 1.234367e-08 9.125697e-09 60 6.697200e-08 1.234367e-08 61 5.364594e-09 6.697200e-08 62 1.119789e-08 5.364594e-09 63 3.189430e-08 1.119789e-08 64 4.846221e-09 3.189430e-08 65 2.437896e-08 4.846221e-09 66 2.685906e-08 2.437896e-08 67 2.066816e-08 2.685906e-08 68 2.473609e-08 2.066816e-08 69 2.010057e-08 2.473609e-08 70 5.562991e-09 2.010057e-08 71 4.069413e-08 5.562991e-09 72 5.354022e-08 4.069413e-08 73 2.497314e-08 5.354022e-08 74 4.227919e-09 2.497314e-08 75 1.765005e-08 4.227919e-09 76 2.615838e-08 1.765005e-08 77 2.001579e-08 2.615838e-08 78 2.144726e-08 2.001579e-08 79 1.543992e-08 2.144726e-08 80 -3.873287e-10 1.543992e-08 81 1.938050e-08 -3.873287e-10 82 2.621988e-08 1.938050e-08 83 2.570844e-09 2.621988e-08 84 4.202183e-08 2.570844e-09 85 2.892279e-09 4.202183e-08 86 1.640503e-08 2.892279e-09 87 -6.934838e-09 1.640503e-08 88 1.625811e-09 -6.934838e-09 89 8.706914e-09 1.625811e-09 90 5.001545e-09 8.706914e-09 91 6.857106e-09 5.001545e-09 92 -3.871455e-09 6.857106e-09 93 -9.765037e-09 -3.871455e-09 94 5.864968e-10 -9.765037e-09 95 6.360928e-09 5.864968e-10 96 3.319089e-08 6.360928e-09 97 -4.694758e-09 3.319089e-08 98 2.055974e-09 -4.694758e-09 99 -1.388847e-09 2.055974e-09 100 9.460992e-10 -1.388847e-09 101 -1.067406e-09 9.460992e-10 102 7.048513e-10 -1.067406e-09 103 -5.669467e-09 7.048513e-10 104 -5.180331e-09 -5.669467e-09 105 -1.235807e-08 -5.180331e-09 106 5.241474e-09 -1.235807e-08 107 3.663050e-09 5.241474e-09 108 8.742033e-10 3.663050e-09 109 -5.377251e-10 8.742033e-10 110 3.827908e-09 -5.377251e-10 111 -7.100834e-09 3.827908e-09 112 -1.466097e-08 -7.100834e-09 113 -2.798492e-08 -1.466097e-08 114 -6.920344e-09 -2.798492e-08 115 -9.782501e-09 -6.920344e-09 116 -2.779208e-09 -9.782501e-09 117 -2.654976e-08 -2.779208e-09 118 -3.133271e-10 -2.654976e-08 119 -2.181285e-08 -3.133271e-10 120 -9.622117e-09 -2.181285e-08 121 -4.336467e-09 -9.622117e-09 122 -3.563200e-08 -4.336467e-09 123 -1.139754e-08 -3.563200e-08 124 -2.788284e-09 -1.139754e-08 125 -7.223223e-09 -2.788284e-09 126 -3.513633e-08 -7.223223e-09 127 -1.182535e-08 -3.513633e-08 128 -8.075961e-09 -1.182535e-08 129 -4.000779e-08 -8.075961e-09 130 -3.666283e-09 -4.000779e-08 131 -3.461573e-08 -3.666283e-09 132 2.001268e-08 -3.461573e-08 133 -6.379200e-09 2.001268e-08 134 -2.166679e-09 -6.379200e-09 135 -1.299459e-08 -2.166679e-09 136 -3.332877e-09 -1.299459e-08 137 -1.385259e-08 -3.332877e-09 138 -1.024563e-08 -1.385259e-08 139 -1.601711e-08 -1.024563e-08 140 -8.778074e-09 -1.601711e-08 141 -1.881244e-08 -8.778074e-09 142 -4.059804e-08 -1.881244e-08 143 -4.188824e-08 -4.059804e-08 144 7.077447e-08 -4.188824e-08 145 -1.316566e-08 7.077447e-08 146 -8.354464e-09 -1.316566e-08 147 -1.839205e-08 -8.354464e-09 148 -9.385693e-09 -1.839205e-08 149 -1.450600e-08 -9.385693e-09 150 3.076635e-08 -1.450600e-08 151 -1.916051e-08 3.076635e-08 152 -1.650788e-08 -1.916051e-08 153 2.403404e-08 -1.650788e-08 154 -8.275833e-09 2.403404e-08 155 4.950264e-08 -8.275833e-09 156 5.700195e-08 4.950264e-08 157 -1.706915e-08 5.700195e-08 158 -7.344715e-09 -1.706915e-08 159 -2.161400e-08 -7.344715e-09 160 -9.712485e-09 -2.161400e-08 161 1.671548e-08 -9.712485e-09 162 -1.946789e-08 1.671548e-08 163 1.203471e-08 -1.946789e-08 164 -1.847189e-08 1.203471e-08 165 1.209636e-08 -1.847189e-08 166 -1.592712e-08 1.209636e-08 167 -1.399349e-08 -1.592712e-08 168 1.176180e-08 -1.399349e-08 169 2.476401e-08 1.176180e-08 170 -4.429559e-10 2.476401e-08 171 -1.478693e-08 -4.429559e-10 172 -2.470116e-09 -1.478693e-08 173 2.101224e-08 -2.470116e-09 174 -9.574275e-09 2.101224e-08 175 1.798283e-08 -9.574275e-09 176 1.756883e-08 1.798283e-08 177 -1.672596e-08 1.756883e-08 178 2.923449e-08 -1.672596e-08 179 3.250480e-08 2.923449e-08 180 1.701627e-08 3.250480e-08 181 -1.231094e-08 1.701627e-08 182 -8.364556e-09 -1.231094e-08 183 -1.751101e-08 -8.364556e-09 184 -1.031320e-08 -1.751101e-08 185 -1.608881e-08 -1.031320e-08 186 -1.507655e-08 -1.608881e-08 187 -2.006185e-08 -1.507655e-08 188 2.878943e-09 -2.006185e-08 189 -3.276543e-09 2.878943e-09 190 -1.166695e-08 -3.276543e-09 191 -4.291769e-09 -1.166695e-08 192 NA -4.291769e-09 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 6.451631e-09 -4.638531e-07 [2,] 1.349050e-08 6.451631e-09 [3,] 3.038542e-09 1.349050e-08 [4,] 8.661236e-09 3.038542e-09 [5,] 3.120701e-09 8.661236e-09 [6,] 3.846301e-09 3.120701e-09 [7,] -1.372984e-09 3.846301e-09 [8,] 7.095257e-09 -1.372984e-09 [9,] 2.435004e-09 7.095257e-09 [10,] 1.521052e-08 2.435004e-09 [11,] 9.372542e-09 1.521052e-08 [12,] 5.017527e-08 9.372542e-09 [13,] -1.452522e-08 5.017527e-08 [14,] 1.974449e-08 -1.452522e-08 [15,] 1.425827e-08 1.974449e-08 [16,] -4.088163e-09 1.425827e-08 [17,] -1.135780e-08 -4.088163e-09 [18,] 1.315455e-08 -1.135780e-08 [19,] 9.925313e-09 1.315455e-08 [20,] -1.081754e-08 9.925313e-09 [21,] 8.885818e-09 -1.081754e-08 [22,] 1.860844e-08 8.885818e-09 [23,] -1.352035e-08 1.860844e-08 [24,] -1.355786e-09 -1.352035e-08 [25,] 1.411336e-08 -1.355786e-09 [26,] 1.713027e-08 1.411336e-08 [27,] 8.310528e-09 1.713027e-08 [28,] 1.563931e-08 8.310528e-09 [29,] 8.474500e-09 1.563931e-08 [30,] 9.172209e-09 8.474500e-09 [31,] -3.762135e-08 9.172209e-09 [32,] -2.244070e-08 -3.762135e-08 [33,] 5.061025e-09 -2.244070e-08 [34,] 1.460007e-08 5.061025e-09 [35,] 1.973140e-08 1.460007e-08 [36,] -1.691038e-08 1.973140e-08 [37,] -4.309236e-08 -1.691038e-08 [38,] -3.783571e-08 -4.309236e-08 [39,] 5.481514e-09 -3.783571e-08 [40,] -4.308668e-08 5.481514e-09 [41,] -4.857399e-08 -4.308668e-08 [42,] -4.952750e-08 -4.857399e-08 [43,] 4.346043e-09 -4.952750e-08 [44,] 8.147808e-09 4.346043e-09 [45,] 1.236177e-09 8.147808e-09 [46,] -4.394251e-08 1.236177e-09 [47,] -4.662156e-08 -4.394251e-08 [48,] 6.839981e-08 -4.662156e-08 [49,] 3.755246e-08 6.839981e-08 [50,] 1.206110e-08 3.755246e-08 [51,] 3.148742e-08 1.206110e-08 [52,] 4.196140e-08 3.148742e-08 [53,] 3.823016e-08 4.196140e-08 [54,] 3.499640e-08 3.823016e-08 [55,] 3.425704e-08 3.499640e-08 [56,] 3.688344e-08 3.425704e-08 [57,] 3.426611e-08 3.688344e-08 [58,] 9.125697e-09 3.426611e-08 [59,] 1.234367e-08 9.125697e-09 [60,] 6.697200e-08 1.234367e-08 [61,] 5.364594e-09 6.697200e-08 [62,] 1.119789e-08 5.364594e-09 [63,] 3.189430e-08 1.119789e-08 [64,] 4.846221e-09 3.189430e-08 [65,] 2.437896e-08 4.846221e-09 [66,] 2.685906e-08 2.437896e-08 [67,] 2.066816e-08 2.685906e-08 [68,] 2.473609e-08 2.066816e-08 [69,] 2.010057e-08 2.473609e-08 [70,] 5.562991e-09 2.010057e-08 [71,] 4.069413e-08 5.562991e-09 [72,] 5.354022e-08 4.069413e-08 [73,] 2.497314e-08 5.354022e-08 [74,] 4.227919e-09 2.497314e-08 [75,] 1.765005e-08 4.227919e-09 [76,] 2.615838e-08 1.765005e-08 [77,] 2.001579e-08 2.615838e-08 [78,] 2.144726e-08 2.001579e-08 [79,] 1.543992e-08 2.144726e-08 [80,] -3.873287e-10 1.543992e-08 [81,] 1.938050e-08 -3.873287e-10 [82,] 2.621988e-08 1.938050e-08 [83,] 2.570844e-09 2.621988e-08 [84,] 4.202183e-08 2.570844e-09 [85,] 2.892279e-09 4.202183e-08 [86,] 1.640503e-08 2.892279e-09 [87,] -6.934838e-09 1.640503e-08 [88,] 1.625811e-09 -6.934838e-09 [89,] 8.706914e-09 1.625811e-09 [90,] 5.001545e-09 8.706914e-09 [91,] 6.857106e-09 5.001545e-09 [92,] -3.871455e-09 6.857106e-09 [93,] -9.765037e-09 -3.871455e-09 [94,] 5.864968e-10 -9.765037e-09 [95,] 6.360928e-09 5.864968e-10 [96,] 3.319089e-08 6.360928e-09 [97,] -4.694758e-09 3.319089e-08 [98,] 2.055974e-09 -4.694758e-09 [99,] -1.388847e-09 2.055974e-09 [100,] 9.460992e-10 -1.388847e-09 [101,] -1.067406e-09 9.460992e-10 [102,] 7.048513e-10 -1.067406e-09 [103,] -5.669467e-09 7.048513e-10 [104,] -5.180331e-09 -5.669467e-09 [105,] -1.235807e-08 -5.180331e-09 [106,] 5.241474e-09 -1.235807e-08 [107,] 3.663050e-09 5.241474e-09 [108,] 8.742033e-10 3.663050e-09 [109,] -5.377251e-10 8.742033e-10 [110,] 3.827908e-09 -5.377251e-10 [111,] -7.100834e-09 3.827908e-09 [112,] -1.466097e-08 -7.100834e-09 [113,] -2.798492e-08 -1.466097e-08 [114,] -6.920344e-09 -2.798492e-08 [115,] -9.782501e-09 -6.920344e-09 [116,] -2.779208e-09 -9.782501e-09 [117,] -2.654976e-08 -2.779208e-09 [118,] -3.133271e-10 -2.654976e-08 [119,] -2.181285e-08 -3.133271e-10 [120,] -9.622117e-09 -2.181285e-08 [121,] -4.336467e-09 -9.622117e-09 [122,] -3.563200e-08 -4.336467e-09 [123,] -1.139754e-08 -3.563200e-08 [124,] -2.788284e-09 -1.139754e-08 [125,] -7.223223e-09 -2.788284e-09 [126,] -3.513633e-08 -7.223223e-09 [127,] -1.182535e-08 -3.513633e-08 [128,] -8.075961e-09 -1.182535e-08 [129,] -4.000779e-08 -8.075961e-09 [130,] -3.666283e-09 -4.000779e-08 [131,] -3.461573e-08 -3.666283e-09 [132,] 2.001268e-08 -3.461573e-08 [133,] -6.379200e-09 2.001268e-08 [134,] -2.166679e-09 -6.379200e-09 [135,] -1.299459e-08 -2.166679e-09 [136,] -3.332877e-09 -1.299459e-08 [137,] -1.385259e-08 -3.332877e-09 [138,] -1.024563e-08 -1.385259e-08 [139,] -1.601711e-08 -1.024563e-08 [140,] -8.778074e-09 -1.601711e-08 [141,] -1.881244e-08 -8.778074e-09 [142,] -4.059804e-08 -1.881244e-08 [143,] -4.188824e-08 -4.059804e-08 [144,] 7.077447e-08 -4.188824e-08 [145,] -1.316566e-08 7.077447e-08 [146,] -8.354464e-09 -1.316566e-08 [147,] -1.839205e-08 -8.354464e-09 [148,] -9.385693e-09 -1.839205e-08 [149,] -1.450600e-08 -9.385693e-09 [150,] 3.076635e-08 -1.450600e-08 [151,] -1.916051e-08 3.076635e-08 [152,] -1.650788e-08 -1.916051e-08 [153,] 2.403404e-08 -1.650788e-08 [154,] -8.275833e-09 2.403404e-08 [155,] 4.950264e-08 -8.275833e-09 [156,] 5.700195e-08 4.950264e-08 [157,] -1.706915e-08 5.700195e-08 [158,] -7.344715e-09 -1.706915e-08 [159,] -2.161400e-08 -7.344715e-09 [160,] -9.712485e-09 -2.161400e-08 [161,] 1.671548e-08 -9.712485e-09 [162,] -1.946789e-08 1.671548e-08 [163,] 1.203471e-08 -1.946789e-08 [164,] -1.847189e-08 1.203471e-08 [165,] 1.209636e-08 -1.847189e-08 [166,] -1.592712e-08 1.209636e-08 [167,] -1.399349e-08 -1.592712e-08 [168,] 1.176180e-08 -1.399349e-08 [169,] 2.476401e-08 1.176180e-08 [170,] -4.429559e-10 2.476401e-08 [171,] -1.478693e-08 -4.429559e-10 [172,] -2.470116e-09 -1.478693e-08 [173,] 2.101224e-08 -2.470116e-09 [174,] -9.574275e-09 2.101224e-08 [175,] 1.798283e-08 -9.574275e-09 [176,] 1.756883e-08 1.798283e-08 [177,] -1.672596e-08 1.756883e-08 [178,] 2.923449e-08 -1.672596e-08 [179,] 3.250480e-08 2.923449e-08 [180,] 1.701627e-08 3.250480e-08 [181,] -1.231094e-08 1.701627e-08 [182,] -8.364556e-09 -1.231094e-08 [183,] -1.751101e-08 -8.364556e-09 [184,] -1.031320e-08 -1.751101e-08 [185,] -1.608881e-08 -1.031320e-08 [186,] -1.507655e-08 -1.608881e-08 [187,] -2.006185e-08 -1.507655e-08 [188,] 2.878943e-09 -2.006185e-08 [189,] -3.276543e-09 2.878943e-09 [190,] -1.166695e-08 -3.276543e-09 [191,] -4.291769e-09 -1.166695e-08 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 6.451631e-09 -4.638531e-07 2 1.349050e-08 6.451631e-09 3 3.038542e-09 1.349050e-08 4 8.661236e-09 3.038542e-09 5 3.120701e-09 8.661236e-09 6 3.846301e-09 3.120701e-09 7 -1.372984e-09 3.846301e-09 8 7.095257e-09 -1.372984e-09 9 2.435004e-09 7.095257e-09 10 1.521052e-08 2.435004e-09 11 9.372542e-09 1.521052e-08 12 5.017527e-08 9.372542e-09 13 -1.452522e-08 5.017527e-08 14 1.974449e-08 -1.452522e-08 15 1.425827e-08 1.974449e-08 16 -4.088163e-09 1.425827e-08 17 -1.135780e-08 -4.088163e-09 18 1.315455e-08 -1.135780e-08 19 9.925313e-09 1.315455e-08 20 -1.081754e-08 9.925313e-09 21 8.885818e-09 -1.081754e-08 22 1.860844e-08 8.885818e-09 23 -1.352035e-08 1.860844e-08 24 -1.355786e-09 -1.352035e-08 25 1.411336e-08 -1.355786e-09 26 1.713027e-08 1.411336e-08 27 8.310528e-09 1.713027e-08 28 1.563931e-08 8.310528e-09 29 8.474500e-09 1.563931e-08 30 9.172209e-09 8.474500e-09 31 -3.762135e-08 9.172209e-09 32 -2.244070e-08 -3.762135e-08 33 5.061025e-09 -2.244070e-08 34 1.460007e-08 5.061025e-09 35 1.973140e-08 1.460007e-08 36 -1.691038e-08 1.973140e-08 37 -4.309236e-08 -1.691038e-08 38 -3.783571e-08 -4.309236e-08 39 5.481514e-09 -3.783571e-08 40 -4.308668e-08 5.481514e-09 41 -4.857399e-08 -4.308668e-08 42 -4.952750e-08 -4.857399e-08 43 4.346043e-09 -4.952750e-08 44 8.147808e-09 4.346043e-09 45 1.236177e-09 8.147808e-09 46 -4.394251e-08 1.236177e-09 47 -4.662156e-08 -4.394251e-08 48 6.839981e-08 -4.662156e-08 49 3.755246e-08 6.839981e-08 50 1.206110e-08 3.755246e-08 51 3.148742e-08 1.206110e-08 52 4.196140e-08 3.148742e-08 53 3.823016e-08 4.196140e-08 54 3.499640e-08 3.823016e-08 55 3.425704e-08 3.499640e-08 56 3.688344e-08 3.425704e-08 57 3.426611e-08 3.688344e-08 58 9.125697e-09 3.426611e-08 59 1.234367e-08 9.125697e-09 60 6.697200e-08 1.234367e-08 61 5.364594e-09 6.697200e-08 62 1.119789e-08 5.364594e-09 63 3.189430e-08 1.119789e-08 64 4.846221e-09 3.189430e-08 65 2.437896e-08 4.846221e-09 66 2.685906e-08 2.437896e-08 67 2.066816e-08 2.685906e-08 68 2.473609e-08 2.066816e-08 69 2.010057e-08 2.473609e-08 70 5.562991e-09 2.010057e-08 71 4.069413e-08 5.562991e-09 72 5.354022e-08 4.069413e-08 73 2.497314e-08 5.354022e-08 74 4.227919e-09 2.497314e-08 75 1.765005e-08 4.227919e-09 76 2.615838e-08 1.765005e-08 77 2.001579e-08 2.615838e-08 78 2.144726e-08 2.001579e-08 79 1.543992e-08 2.144726e-08 80 -3.873287e-10 1.543992e-08 81 1.938050e-08 -3.873287e-10 82 2.621988e-08 1.938050e-08 83 2.570844e-09 2.621988e-08 84 4.202183e-08 2.570844e-09 85 2.892279e-09 4.202183e-08 86 1.640503e-08 2.892279e-09 87 -6.934838e-09 1.640503e-08 88 1.625811e-09 -6.934838e-09 89 8.706914e-09 1.625811e-09 90 5.001545e-09 8.706914e-09 91 6.857106e-09 5.001545e-09 92 -3.871455e-09 6.857106e-09 93 -9.765037e-09 -3.871455e-09 94 5.864968e-10 -9.765037e-09 95 6.360928e-09 5.864968e-10 96 3.319089e-08 6.360928e-09 97 -4.694758e-09 3.319089e-08 98 2.055974e-09 -4.694758e-09 99 -1.388847e-09 2.055974e-09 100 9.460992e-10 -1.388847e-09 101 -1.067406e-09 9.460992e-10 102 7.048513e-10 -1.067406e-09 103 -5.669467e-09 7.048513e-10 104 -5.180331e-09 -5.669467e-09 105 -1.235807e-08 -5.180331e-09 106 5.241474e-09 -1.235807e-08 107 3.663050e-09 5.241474e-09 108 8.742033e-10 3.663050e-09 109 -5.377251e-10 8.742033e-10 110 3.827908e-09 -5.377251e-10 111 -7.100834e-09 3.827908e-09 112 -1.466097e-08 -7.100834e-09 113 -2.798492e-08 -1.466097e-08 114 -6.920344e-09 -2.798492e-08 115 -9.782501e-09 -6.920344e-09 116 -2.779208e-09 -9.782501e-09 117 -2.654976e-08 -2.779208e-09 118 -3.133271e-10 -2.654976e-08 119 -2.181285e-08 -3.133271e-10 120 -9.622117e-09 -2.181285e-08 121 -4.336467e-09 -9.622117e-09 122 -3.563200e-08 -4.336467e-09 123 -1.139754e-08 -3.563200e-08 124 -2.788284e-09 -1.139754e-08 125 -7.223223e-09 -2.788284e-09 126 -3.513633e-08 -7.223223e-09 127 -1.182535e-08 -3.513633e-08 128 -8.075961e-09 -1.182535e-08 129 -4.000779e-08 -8.075961e-09 130 -3.666283e-09 -4.000779e-08 131 -3.461573e-08 -3.666283e-09 132 2.001268e-08 -3.461573e-08 133 -6.379200e-09 2.001268e-08 134 -2.166679e-09 -6.379200e-09 135 -1.299459e-08 -2.166679e-09 136 -3.332877e-09 -1.299459e-08 137 -1.385259e-08 -3.332877e-09 138 -1.024563e-08 -1.385259e-08 139 -1.601711e-08 -1.024563e-08 140 -8.778074e-09 -1.601711e-08 141 -1.881244e-08 -8.778074e-09 142 -4.059804e-08 -1.881244e-08 143 -4.188824e-08 -4.059804e-08 144 7.077447e-08 -4.188824e-08 145 -1.316566e-08 7.077447e-08 146 -8.354464e-09 -1.316566e-08 147 -1.839205e-08 -8.354464e-09 148 -9.385693e-09 -1.839205e-08 149 -1.450600e-08 -9.385693e-09 150 3.076635e-08 -1.450600e-08 151 -1.916051e-08 3.076635e-08 152 -1.650788e-08 -1.916051e-08 153 2.403404e-08 -1.650788e-08 154 -8.275833e-09 2.403404e-08 155 4.950264e-08 -8.275833e-09 156 5.700195e-08 4.950264e-08 157 -1.706915e-08 5.700195e-08 158 -7.344715e-09 -1.706915e-08 159 -2.161400e-08 -7.344715e-09 160 -9.712485e-09 -2.161400e-08 161 1.671548e-08 -9.712485e-09 162 -1.946789e-08 1.671548e-08 163 1.203471e-08 -1.946789e-08 164 -1.847189e-08 1.203471e-08 165 1.209636e-08 -1.847189e-08 166 -1.592712e-08 1.209636e-08 167 -1.399349e-08 -1.592712e-08 168 1.176180e-08 -1.399349e-08 169 2.476401e-08 1.176180e-08 170 -4.429559e-10 2.476401e-08 171 -1.478693e-08 -4.429559e-10 172 -2.470116e-09 -1.478693e-08 173 2.101224e-08 -2.470116e-09 174 -9.574275e-09 2.101224e-08 175 1.798283e-08 -9.574275e-09 176 1.756883e-08 1.798283e-08 177 -1.672596e-08 1.756883e-08 178 2.923449e-08 -1.672596e-08 179 3.250480e-08 2.923449e-08 180 1.701627e-08 3.250480e-08 181 -1.231094e-08 1.701627e-08 182 -8.364556e-09 -1.231094e-08 183 -1.751101e-08 -8.364556e-09 184 -1.031320e-08 -1.751101e-08 185 -1.608881e-08 -1.031320e-08 186 -1.507655e-08 -1.608881e-08 187 -2.006185e-08 -1.507655e-08 188 2.878943e-09 -2.006185e-08 189 -3.276543e-09 2.878943e-09 190 -1.166695e-08 -3.276543e-09 191 -4.291769e-09 -1.166695e-08 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/7osm21227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/81y8g1227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9hdvw1227532732.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/10aey51227532732.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11pxi11227532732.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/120p8q1227532732.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/133z1t1227532732.tab") > system("convert tmp/1241x1227532732.ps tmp/1241x1227532732.png") > system("convert tmp/2gncz1227532732.ps tmp/2gncz1227532732.png") > system("convert tmp/38vl51227532732.ps tmp/38vl51227532732.png") > system("convert tmp/4sf071227532732.ps tmp/4sf071227532732.png") > system("convert tmp/5mddd1227532732.ps tmp/5mddd1227532732.png") > system("convert tmp/65t271227532732.ps tmp/65t271227532732.png") > system("convert tmp/7osm21227532732.ps tmp/7osm21227532732.png") > system("convert tmp/81y8g1227532732.ps tmp/81y8g1227532732.png") > system("convert tmp/9hdvw1227532732.ps tmp/9hdvw1227532732.png") > > > proc.time() user system elapsed 2.688 1.596 6.764