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Type 'q()' to quit R. > x <- array(list(1687 + ,0 + ,-183.9235445 + ,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('Cons' + ,'Inc' + ,'Price') + ,1:192)) > y <- array(NA,dim=c(3,192),dimnames=list(c('Cons','Inc','Price'),1:192)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > #'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) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > 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 Cons Inc Price M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 1687 0 -183.9235445 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) Inc Price 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 -4.858e-08 -1.016e-08 -5.284e-10 9.344e-09 4.904e-08 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.324e+03 5.929e-09 3.920e+11 <2e-16 *** Inc -2.264e+02 5.526e-09 -4.097e+10 <2e-16 *** Price 1.000e+00 1.009e-11 9.908e+10 <2e-16 *** M1 -4.514e+02 7.264e-09 -6.214e+10 <2e-16 *** M2 -6.355e+02 7.263e-09 -8.749e+10 <2e-16 *** M3 -5.831e+02 7.262e-09 -8.030e+10 <2e-16 *** M4 -6.946e+02 7.261e-09 -9.566e+10 <2e-16 *** M5 -5.555e+02 7.260e-09 -7.651e+10 <2e-16 *** M6 -6.095e+02 7.259e-09 -8.396e+10 <2e-16 *** M7 -5.321e+02 7.258e-09 -7.331e+10 <2e-16 *** M8 -5.154e+02 7.257e-09 -7.102e+10 <2e-16 *** M9 -4.609e+02 7.257e-09 -6.351e+10 <2e-16 *** M10 -3.197e+02 7.257e-09 -4.406e+10 <2e-16 *** M11 -1.184e+02 7.256e-09 -1.632e+10 <2e-16 *** t -1.765e+00 3.239e-11 -5.449e+10 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.052e-08 on 177 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 2.717e+21 on 14 and 177 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.25441635 5.088327e-01 7.455837e-01 [2,] 0.13936807 2.787361e-01 8.606319e-01 [3,] 0.07771399 1.554280e-01 9.222860e-01 [4,] 0.06010793 1.202159e-01 9.398921e-01 [5,] 0.02814297 5.628594e-02 9.718570e-01 [6,] 0.01341643 2.683286e-02 9.865836e-01 [7,] 0.01784442 3.568884e-02 9.821556e-01 [8,] 0.07591480 1.518296e-01 9.240852e-01 [9,] 0.07292324 1.458465e-01 9.270768e-01 [10,] 0.04452423 8.904846e-02 9.554758e-01 [11,] 0.02636861 5.273721e-02 9.736314e-01 [12,] 0.02245331 4.490662e-02 9.775467e-01 [13,] 0.01791796 3.583592e-02 9.820820e-01 [14,] 0.01024981 2.049962e-02 9.897502e-01 [15,] 0.03571731 7.143462e-02 9.642827e-01 [16,] 0.04097815 8.195629e-02 9.590219e-01 [17,] 0.02715752 5.431505e-02 9.728425e-01 [18,] 0.01726999 3.453997e-02 9.827300e-01 [19,] 0.01463093 2.926185e-02 9.853691e-01 [20,] 0.04303351 8.606701e-02 9.569665e-01 [21,] 0.10227549 2.045510e-01 8.977245e-01 [22,] 0.20464653 4.092931e-01 7.953535e-01 [23,] 0.16653482 3.330696e-01 8.334652e-01 [24,] 0.22631032 4.526206e-01 7.736897e-01 [25,] 0.31861581 6.372316e-01 6.813842e-01 [26,] 0.48831761 9.766352e-01 5.116824e-01 [27,] 0.46896387 9.379277e-01 5.310361e-01 [28,] 0.53038118 9.392376e-01 4.696188e-01 [29,] 0.48688388 9.737678e-01 5.131161e-01 [30,] 0.69286022 6.142796e-01 3.071398e-01 [31,] 0.79884566 4.023087e-01 2.011543e-01 [32,] 0.97217740 5.564521e-02 2.782260e-02 [33,] 0.99642741 7.145176e-03 3.572588e-03 [34,] 0.99492246 1.015507e-02 5.077537e-03 [35,] 0.99798584 4.028320e-03 2.014160e-03 [36,] 0.99957905 8.418976e-04 4.209488e-04 [37,] 0.99985437 2.912570e-04 1.456285e-04 [38,] 0.99993096 1.380850e-04 6.904250e-05 [39,] 0.99995271 9.458113e-05 4.729056e-05 [40,] 0.99998608 2.783717e-05 1.391858e-05 [41,] 0.99998819 2.361452e-05 1.180726e-05 [42,] 0.99998207 3.586296e-05 1.793148e-05 [43,] 0.99997100 5.800008e-05 2.900004e-05 [44,] 0.99996077 7.845376e-05 3.922688e-05 [45,] 0.99995039 9.922696e-05 4.961348e-05 [46,] 0.99992644 1.471193e-04 7.355965e-05 [47,] 0.99991279 1.744294e-04 8.721470e-05 [48,] 0.99987387 2.522595e-04 1.261297e-04 [49,] 0.99985740 2.851918e-04 1.425959e-04 [50,] 0.99983700 3.260064e-04 1.630032e-04 [51,] 0.99980191 3.961831e-04 1.980915e-04 [52,] 0.99982365 3.527015e-04 1.763507e-04 [53,] 0.99982050 3.590057e-04 1.795028e-04 [54,] 0.99975277 4.944632e-04 2.472316e-04 [55,] 0.99979499 4.100162e-04 2.050081e-04 [56,] 0.99972169 5.566159e-04 2.783080e-04 [57,] 0.99962752 7.449526e-04 3.724763e-04 [58,] 0.99951369 9.726299e-04 4.863150e-04 [59,] 0.99949196 1.016087e-03 5.080436e-04 [60,] 0.99944727 1.105461e-03 5.527306e-04 [61,] 0.99927578 1.448434e-03 7.242170e-04 [62,] 0.99913334 1.733321e-03 8.666603e-04 [63,] 0.99890799 2.184022e-03 1.092011e-03 [64,] 0.99871756 2.564877e-03 1.282439e-03 [65,] 0.99846940 3.061205e-03 1.530603e-03 [66,] 0.99839991 3.200184e-03 1.600092e-03 [67,] 0.99792066 4.158673e-03 2.079336e-03 [68,] 0.99734959 5.300810e-03 2.650405e-03 [69,] 0.99679929 6.401413e-03 3.200707e-03 [70,] 0.99607445 7.851101e-03 3.925551e-03 [71,] 0.99647239 7.055219e-03 3.527610e-03 [72,] 0.99578494 8.430116e-03 4.215058e-03 [73,] 0.99453758 1.092483e-02 5.462415e-03 [74,] 0.99356753 1.286494e-02 6.432469e-03 [75,] 0.99190315 1.619369e-02 8.096846e-03 [76,] 0.99021616 1.956768e-02 9.783839e-03 [77,] 0.99000597 1.998806e-02 9.994028e-03 [78,] 0.98764439 2.471122e-02 1.235561e-02 [79,] 0.98609401 2.781199e-02 1.390599e-02 [80,] 0.98295336 3.409327e-02 1.704664e-02 [81,] 0.97939350 4.121300e-02 2.060650e-02 [82,] 0.97459030 5.081941e-02 2.540970e-02 [83,] 0.97255431 5.489138e-02 2.744569e-02 [84,] 0.96669009 6.661982e-02 3.330991e-02 [85,] 0.95988325 8.023350e-02 4.011675e-02 [86,] 0.95405600 9.188801e-02 4.594400e-02 [87,] 0.94616426 1.076715e-01 5.383574e-02 [88,] 0.93581514 1.283697e-01 6.418486e-02 [89,] 0.93023947 1.395211e-01 6.976053e-02 [90,] 0.92371472 1.525706e-01 7.628528e-02 [91,] 0.91962730 1.607454e-01 8.037270e-02 [92,] 0.91947199 1.610560e-01 8.052801e-02 [93,] 0.90554588 1.889082e-01 9.445412e-02 [94,] 0.89826442 2.034712e-01 1.017356e-01 [95,] 0.89377838 2.124432e-01 1.062216e-01 [96,] 0.88142124 2.371575e-01 1.185788e-01 [97,] 0.87875376 2.424925e-01 1.212462e-01 [98,] 0.86766921 2.646616e-01 1.323308e-01 [99,] 0.84778329 3.044334e-01 1.522167e-01 [100,] 0.82456950 3.508610e-01 1.754305e-01 [101,] 0.83060324 3.387935e-01 1.693968e-01 [102,] 0.82588929 3.482214e-01 1.741107e-01 [103,] 0.80571093 3.885781e-01 1.942891e-01 [104,] 0.82946069 3.410786e-01 1.705393e-01 [105,] 0.80202161 3.959568e-01 1.979784e-01 [106,] 0.79856563 4.028687e-01 2.014344e-01 [107,] 0.78032574 4.393485e-01 2.196743e-01 [108,] 0.75394543 4.921091e-01 2.460546e-01 [109,] 0.71501101 5.699780e-01 2.849890e-01 [110,] 0.74882659 5.023468e-01 2.511734e-01 [111,] 0.71068602 5.786280e-01 2.893140e-01 [112,] 0.66843380 6.631324e-01 3.315662e-01 [113,] 0.77485311 4.502938e-01 2.251469e-01 [114,] 0.75679555 4.864089e-01 2.432044e-01 [115,] 0.75081794 4.983641e-01 2.491821e-01 [116,] 0.71538196 5.692361e-01 2.846180e-01 [117,] 0.67102546 6.579491e-01 3.289745e-01 [118,] 0.62635327 7.472935e-01 3.736467e-01 [119,] 0.58324548 8.335090e-01 4.167545e-01 [120,] 0.53360621 9.327876e-01 4.663938e-01 [121,] 0.48796840 9.759368e-01 5.120316e-01 [122,] 0.44023039 8.804608e-01 5.597696e-01 [123,] 0.40101949 8.020390e-01 5.989805e-01 [124,] 0.35737796 7.147559e-01 6.426220e-01 [125,] 0.35293996 7.058799e-01 6.470600e-01 [126,] 0.54781255 9.043749e-01 4.521875e-01 [127,] 0.88685098 2.262980e-01 1.131490e-01 [128,] 0.90859360 1.828128e-01 9.140640e-02 [129,] 0.89769258 2.046148e-01 1.023074e-01 [130,] 0.87497369 2.500526e-01 1.250263e-01 [131,] 0.84939079 3.012184e-01 1.506092e-01 [132,] 0.82179175 3.564165e-01 1.782083e-01 [133,] 0.86726161 2.654768e-01 1.327384e-01 [134,] 0.93457070 1.308586e-01 6.542930e-02 [135,] 0.96074898 7.850204e-02 3.925102e-02 [136,] 0.97368079 5.263843e-02 2.631921e-02 [137,] 0.97411121 5.177757e-02 2.588879e-02 [138,] 0.97994418 4.011163e-02 2.005582e-02 [139,] 0.98275796 3.448409e-02 1.724204e-02 [140,] 0.98832389 2.335223e-02 1.167611e-02 [141,] 0.98593532 2.812935e-02 1.406468e-02 [142,] 0.97717097 4.565807e-02 2.282903e-02 [143,] 0.96491562 7.016877e-02 3.508438e-02 [144,] 0.94599234 1.080153e-01 5.400766e-02 [145,] 0.95278069 9.443863e-02 4.721931e-02 [146,] 0.92792076 1.441585e-01 7.207924e-02 [147,] 0.96149440 7.701120e-02 3.850560e-02 [148,] 0.98558576 2.882847e-02 1.441424e-02 [149,] 0.99765810 4.683797e-03 2.341898e-03 [150,] 0.99450674 1.098652e-02 5.493259e-03 [151,] 0.98956953 2.086095e-02 1.043047e-02 [152,] 0.97734843 4.530314e-02 2.265157e-02 [153,] 0.97029627 5.940746e-02 2.970373e-02 [154,] 0.94043113 1.191377e-01 5.956887e-02 [155,] 0.88955487 2.208903e-01 1.104451e-01 [156,] 0.79435357 4.112929e-01 2.056464e-01 [157,] 0.73480717 5.303857e-01 2.651928e-01 > postscript(file="/var/www/html/freestat/rcomp/tmp/1dl2t1227834072.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2xqu91227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/freestat/rcomp/tmp/3w0k41227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4qd7g1227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5bczt1227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 192 Frequency = 1 1 2 3 4 5 -8.094662e-09 -5.836723e-09 5.543537e-11 -1.059642e-08 -2.532605e-09 6 7 8 9 10 -9.523272e-09 -9.414170e-09 -1.338654e-08 -7.223964e-09 -1.333926e-08 11 12 13 14 15 6.096096e-09 -2.424756e-09 9.123620e-09 -1.937498e-08 1.270383e-08 16 17 18 19 20 6.198129e-09 -1.482399e-08 -2.207696e-08 7.091596e-09 3.420478e-09 21 22 23 24 25 -2.029817e-08 2.732710e-09 1.322114e-08 -1.625306e-08 -3.449853e-08 26 27 28 29 30 8.543845e-09 1.128128e-08 3.422160e-09 1.174477e-08 4.507621e-09 31 32 33 34 35 4.613464e-09 -3.959767e-08 -3.241888e-08 2.783303e-10 1.073880e-08 36 37 38 39 40 1.236481e-08 -4.721491e-08 -4.442280e-08 -3.880062e-08 1.118771e-09 41 42 43 44 45 -4.145219e-08 -4.843513e-08 -4.857950e-08 -1.174581e-09 3.431793e-09 46 47 48 49 50 -2.176002e-09 -4.243028e-08 -4.198759e-08 4.019968e-08 4.228494e-08 51 52 53 54 55 9.309018e-09 3.712360e-08 4.592267e-08 3.920573e-08 3.871591e-08 56 57 58 59 60 3.542212e-08 4.069877e-08 3.489312e-08 6.159635e-09 7.495692e-09 61 62 63 64 65 2.962354e-08 1.593709e-09 7.303306e-09 2.682547e-08 4.484874e-09 66 67 68 69 70 2.674752e-08 2.712326e-08 2.300350e-08 2.849846e-08 2.238708e-08 71 72 73 74 75 3.744966e-09 3.537082e-08 1.722867e-08 1.965954e-08 4.372377e-09 76 77 78 79 80 1.430760e-08 2.280885e-08 1.572657e-08 1.594347e-08 1.185149e-08 81 82 83 84 85 -2.637431e-09 1.191816e-08 2.196962e-08 2.265323e-09 5.123779e-09 86 87 88 89 90 5.954249e-09 1.282746e-08 -8.261983e-09 2.472822e-10 3.653507e-09 91 92 93 94 95 3.092123e-09 1.913903e-10 -5.040097e-09 -1.134230e-08 -7.586712e-10 96 97 98 99 100 9.449693e-09 1.910949e-09 -5.555003e-09 2.935931e-10 -8.116539e-10 101 102 103 104 105 -1.730608e-09 2.976905e-10 5.663588e-10 -3.581396e-09 -7.113432e-09 106 107 108 109 110 -1.361006e-08 6.556555e-09 7.165935e-09 -2.183001e-08 1.684860e-09 111 112 113 114 115 7.172029e-09 -3.551862e-09 -1.445504e-08 -2.262527e-08 -2.463934e-09 116 117 118 119 120 -6.079434e-09 -1.396753e-10 -2.612002e-08 3.840122e-09 -1.553859e-08 121 122 123 124 125 -3.378005e-08 -7.655050e-10 -2.613607e-08 -6.077702e-09 1.590332e-09 126 127 128 129 130 -4.384753e-09 -3.406845e-08 -8.263837e-09 -3.665420e-09 -3.851876e-08 131 132 133 134 135 1.457278e-09 -2.783805e-08 -5.710233e-09 -2.949895e-09 3.362692e-09 136 137 138 139 140 -8.194687e-09 4.815177e-10 -7.263926e-09 -6.717435e-09 -1.077389e-08 141 142 143 144 145 -4.798097e-09 -1.172763e-08 -3.995278e-08 -3.929975e-08 4.253027e-08 146 147 148 149 150 -5.852915e-09 -2.982267e-10 -1.088724e-08 -2.310356e-09 -9.237841e-09 151 152 153 154 155 4.004591e-08 -1.312483e-08 -7.844214e-09 3.531368e-08 -2.990728e-09 156 157 158 159 160 4.903607e-08 3.008395e-08 -8.319161e-09 5.254581e-10 -1.325027e-08 161 162 163 164 165 -1.689410e-09 2.755725e-08 -1.186442e-08 2.366629e-08 -1.001670e-08 166 167 168 169 170 2.314532e-08 -6.024919e-09 -4.883586e-09 -1.258494e-08 2.315130e-08 171 172 173 174 175 4.002466e-10 -1.253815e-08 -1.762995e-09 1.940102e-08 -1.068786e-08 176 177 178 179 180 1.576027e-08 2.057624e-08 -1.548356e-08 2.594977e-08 2.729383e-08 181 182 183 184 185 -1.211112e-08 -9.795453e-09 -4.371815e-09 -1.482576e-08 -6.523110e-09 186 187 188 189 190 -1.354976e-08 -1.339632e-08 -1.733337e-08 7.990811e-09 1.649192e-09 191 192 -7.576603e-09 -2.216798e-09 > postscript(file="/var/www/html/freestat/rcomp/tmp/6ejrg1227834072.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 -8.094662e-09 NA 1 -5.836723e-09 -8.094662e-09 2 5.543537e-11 -5.836723e-09 3 -1.059642e-08 5.543537e-11 4 -2.532605e-09 -1.059642e-08 5 -9.523272e-09 -2.532605e-09 6 -9.414170e-09 -9.523272e-09 7 -1.338654e-08 -9.414170e-09 8 -7.223964e-09 -1.338654e-08 9 -1.333926e-08 -7.223964e-09 10 6.096096e-09 -1.333926e-08 11 -2.424756e-09 6.096096e-09 12 9.123620e-09 -2.424756e-09 13 -1.937498e-08 9.123620e-09 14 1.270383e-08 -1.937498e-08 15 6.198129e-09 1.270383e-08 16 -1.482399e-08 6.198129e-09 17 -2.207696e-08 -1.482399e-08 18 7.091596e-09 -2.207696e-08 19 3.420478e-09 7.091596e-09 20 -2.029817e-08 3.420478e-09 21 2.732710e-09 -2.029817e-08 22 1.322114e-08 2.732710e-09 23 -1.625306e-08 1.322114e-08 24 -3.449853e-08 -1.625306e-08 25 8.543845e-09 -3.449853e-08 26 1.128128e-08 8.543845e-09 27 3.422160e-09 1.128128e-08 28 1.174477e-08 3.422160e-09 29 4.507621e-09 1.174477e-08 30 4.613464e-09 4.507621e-09 31 -3.959767e-08 4.613464e-09 32 -3.241888e-08 -3.959767e-08 33 2.783303e-10 -3.241888e-08 34 1.073880e-08 2.783303e-10 35 1.236481e-08 1.073880e-08 36 -4.721491e-08 1.236481e-08 37 -4.442280e-08 -4.721491e-08 38 -3.880062e-08 -4.442280e-08 39 1.118771e-09 -3.880062e-08 40 -4.145219e-08 1.118771e-09 41 -4.843513e-08 -4.145219e-08 42 -4.857950e-08 -4.843513e-08 43 -1.174581e-09 -4.857950e-08 44 3.431793e-09 -1.174581e-09 45 -2.176002e-09 3.431793e-09 46 -4.243028e-08 -2.176002e-09 47 -4.198759e-08 -4.243028e-08 48 4.019968e-08 -4.198759e-08 49 4.228494e-08 4.019968e-08 50 9.309018e-09 4.228494e-08 51 3.712360e-08 9.309018e-09 52 4.592267e-08 3.712360e-08 53 3.920573e-08 4.592267e-08 54 3.871591e-08 3.920573e-08 55 3.542212e-08 3.871591e-08 56 4.069877e-08 3.542212e-08 57 3.489312e-08 4.069877e-08 58 6.159635e-09 3.489312e-08 59 7.495692e-09 6.159635e-09 60 2.962354e-08 7.495692e-09 61 1.593709e-09 2.962354e-08 62 7.303306e-09 1.593709e-09 63 2.682547e-08 7.303306e-09 64 4.484874e-09 2.682547e-08 65 2.674752e-08 4.484874e-09 66 2.712326e-08 2.674752e-08 67 2.300350e-08 2.712326e-08 68 2.849846e-08 2.300350e-08 69 2.238708e-08 2.849846e-08 70 3.744966e-09 2.238708e-08 71 3.537082e-08 3.744966e-09 72 1.722867e-08 3.537082e-08 73 1.965954e-08 1.722867e-08 74 4.372377e-09 1.965954e-08 75 1.430760e-08 4.372377e-09 76 2.280885e-08 1.430760e-08 77 1.572657e-08 2.280885e-08 78 1.594347e-08 1.572657e-08 79 1.185149e-08 1.594347e-08 80 -2.637431e-09 1.185149e-08 81 1.191816e-08 -2.637431e-09 82 2.196962e-08 1.191816e-08 83 2.265323e-09 2.196962e-08 84 5.123779e-09 2.265323e-09 85 5.954249e-09 5.123779e-09 86 1.282746e-08 5.954249e-09 87 -8.261983e-09 1.282746e-08 88 2.472822e-10 -8.261983e-09 89 3.653507e-09 2.472822e-10 90 3.092123e-09 3.653507e-09 91 1.913903e-10 3.092123e-09 92 -5.040097e-09 1.913903e-10 93 -1.134230e-08 -5.040097e-09 94 -7.586712e-10 -1.134230e-08 95 9.449693e-09 -7.586712e-10 96 1.910949e-09 9.449693e-09 97 -5.555003e-09 1.910949e-09 98 2.935931e-10 -5.555003e-09 99 -8.116539e-10 2.935931e-10 100 -1.730608e-09 -8.116539e-10 101 2.976905e-10 -1.730608e-09 102 5.663588e-10 2.976905e-10 103 -3.581396e-09 5.663588e-10 104 -7.113432e-09 -3.581396e-09 105 -1.361006e-08 -7.113432e-09 106 6.556555e-09 -1.361006e-08 107 7.165935e-09 6.556555e-09 108 -2.183001e-08 7.165935e-09 109 1.684860e-09 -2.183001e-08 110 7.172029e-09 1.684860e-09 111 -3.551862e-09 7.172029e-09 112 -1.445504e-08 -3.551862e-09 113 -2.262527e-08 -1.445504e-08 114 -2.463934e-09 -2.262527e-08 115 -6.079434e-09 -2.463934e-09 116 -1.396753e-10 -6.079434e-09 117 -2.612002e-08 -1.396753e-10 118 3.840122e-09 -2.612002e-08 119 -1.553859e-08 3.840122e-09 120 -3.378005e-08 -1.553859e-08 121 -7.655050e-10 -3.378005e-08 122 -2.613607e-08 -7.655050e-10 123 -6.077702e-09 -2.613607e-08 124 1.590332e-09 -6.077702e-09 125 -4.384753e-09 1.590332e-09 126 -3.406845e-08 -4.384753e-09 127 -8.263837e-09 -3.406845e-08 128 -3.665420e-09 -8.263837e-09 129 -3.851876e-08 -3.665420e-09 130 1.457278e-09 -3.851876e-08 131 -2.783805e-08 1.457278e-09 132 -5.710233e-09 -2.783805e-08 133 -2.949895e-09 -5.710233e-09 134 3.362692e-09 -2.949895e-09 135 -8.194687e-09 3.362692e-09 136 4.815177e-10 -8.194687e-09 137 -7.263926e-09 4.815177e-10 138 -6.717435e-09 -7.263926e-09 139 -1.077389e-08 -6.717435e-09 140 -4.798097e-09 -1.077389e-08 141 -1.172763e-08 -4.798097e-09 142 -3.995278e-08 -1.172763e-08 143 -3.929975e-08 -3.995278e-08 144 4.253027e-08 -3.929975e-08 145 -5.852915e-09 4.253027e-08 146 -2.982267e-10 -5.852915e-09 147 -1.088724e-08 -2.982267e-10 148 -2.310356e-09 -1.088724e-08 149 -9.237841e-09 -2.310356e-09 150 4.004591e-08 -9.237841e-09 151 -1.312483e-08 4.004591e-08 152 -7.844214e-09 -1.312483e-08 153 3.531368e-08 -7.844214e-09 154 -2.990728e-09 3.531368e-08 155 4.903607e-08 -2.990728e-09 156 3.008395e-08 4.903607e-08 157 -8.319161e-09 3.008395e-08 158 5.254581e-10 -8.319161e-09 159 -1.325027e-08 5.254581e-10 160 -1.689410e-09 -1.325027e-08 161 2.755725e-08 -1.689410e-09 162 -1.186442e-08 2.755725e-08 163 2.366629e-08 -1.186442e-08 164 -1.001670e-08 2.366629e-08 165 2.314532e-08 -1.001670e-08 166 -6.024919e-09 2.314532e-08 167 -4.883586e-09 -6.024919e-09 168 -1.258494e-08 -4.883586e-09 169 2.315130e-08 -1.258494e-08 170 4.002466e-10 2.315130e-08 171 -1.253815e-08 4.002466e-10 172 -1.762995e-09 -1.253815e-08 173 1.940102e-08 -1.762995e-09 174 -1.068786e-08 1.940102e-08 175 1.576027e-08 -1.068786e-08 176 2.057624e-08 1.576027e-08 177 -1.548356e-08 2.057624e-08 178 2.594977e-08 -1.548356e-08 179 2.729383e-08 2.594977e-08 180 -1.211112e-08 2.729383e-08 181 -9.795453e-09 -1.211112e-08 182 -4.371815e-09 -9.795453e-09 183 -1.482576e-08 -4.371815e-09 184 -6.523110e-09 -1.482576e-08 185 -1.354976e-08 -6.523110e-09 186 -1.339632e-08 -1.354976e-08 187 -1.733337e-08 -1.339632e-08 188 7.990811e-09 -1.733337e-08 189 1.649192e-09 7.990811e-09 190 -7.576603e-09 1.649192e-09 191 -2.216798e-09 -7.576603e-09 192 NA -2.216798e-09 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -5.836723e-09 -8.094662e-09 [2,] 5.543537e-11 -5.836723e-09 [3,] -1.059642e-08 5.543537e-11 [4,] -2.532605e-09 -1.059642e-08 [5,] -9.523272e-09 -2.532605e-09 [6,] -9.414170e-09 -9.523272e-09 [7,] -1.338654e-08 -9.414170e-09 [8,] -7.223964e-09 -1.338654e-08 [9,] -1.333926e-08 -7.223964e-09 [10,] 6.096096e-09 -1.333926e-08 [11,] -2.424756e-09 6.096096e-09 [12,] 9.123620e-09 -2.424756e-09 [13,] -1.937498e-08 9.123620e-09 [14,] 1.270383e-08 -1.937498e-08 [15,] 6.198129e-09 1.270383e-08 [16,] -1.482399e-08 6.198129e-09 [17,] -2.207696e-08 -1.482399e-08 [18,] 7.091596e-09 -2.207696e-08 [19,] 3.420478e-09 7.091596e-09 [20,] -2.029817e-08 3.420478e-09 [21,] 2.732710e-09 -2.029817e-08 [22,] 1.322114e-08 2.732710e-09 [23,] -1.625306e-08 1.322114e-08 [24,] -3.449853e-08 -1.625306e-08 [25,] 8.543845e-09 -3.449853e-08 [26,] 1.128128e-08 8.543845e-09 [27,] 3.422160e-09 1.128128e-08 [28,] 1.174477e-08 3.422160e-09 [29,] 4.507621e-09 1.174477e-08 [30,] 4.613464e-09 4.507621e-09 [31,] -3.959767e-08 4.613464e-09 [32,] -3.241888e-08 -3.959767e-08 [33,] 2.783303e-10 -3.241888e-08 [34,] 1.073880e-08 2.783303e-10 [35,] 1.236481e-08 1.073880e-08 [36,] -4.721491e-08 1.236481e-08 [37,] -4.442280e-08 -4.721491e-08 [38,] -3.880062e-08 -4.442280e-08 [39,] 1.118771e-09 -3.880062e-08 [40,] -4.145219e-08 1.118771e-09 [41,] -4.843513e-08 -4.145219e-08 [42,] -4.857950e-08 -4.843513e-08 [43,] -1.174581e-09 -4.857950e-08 [44,] 3.431793e-09 -1.174581e-09 [45,] -2.176002e-09 3.431793e-09 [46,] -4.243028e-08 -2.176002e-09 [47,] -4.198759e-08 -4.243028e-08 [48,] 4.019968e-08 -4.198759e-08 [49,] 4.228494e-08 4.019968e-08 [50,] 9.309018e-09 4.228494e-08 [51,] 3.712360e-08 9.309018e-09 [52,] 4.592267e-08 3.712360e-08 [53,] 3.920573e-08 4.592267e-08 [54,] 3.871591e-08 3.920573e-08 [55,] 3.542212e-08 3.871591e-08 [56,] 4.069877e-08 3.542212e-08 [57,] 3.489312e-08 4.069877e-08 [58,] 6.159635e-09 3.489312e-08 [59,] 7.495692e-09 6.159635e-09 [60,] 2.962354e-08 7.495692e-09 [61,] 1.593709e-09 2.962354e-08 [62,] 7.303306e-09 1.593709e-09 [63,] 2.682547e-08 7.303306e-09 [64,] 4.484874e-09 2.682547e-08 [65,] 2.674752e-08 4.484874e-09 [66,] 2.712326e-08 2.674752e-08 [67,] 2.300350e-08 2.712326e-08 [68,] 2.849846e-08 2.300350e-08 [69,] 2.238708e-08 2.849846e-08 [70,] 3.744966e-09 2.238708e-08 [71,] 3.537082e-08 3.744966e-09 [72,] 1.722867e-08 3.537082e-08 [73,] 1.965954e-08 1.722867e-08 [74,] 4.372377e-09 1.965954e-08 [75,] 1.430760e-08 4.372377e-09 [76,] 2.280885e-08 1.430760e-08 [77,] 1.572657e-08 2.280885e-08 [78,] 1.594347e-08 1.572657e-08 [79,] 1.185149e-08 1.594347e-08 [80,] -2.637431e-09 1.185149e-08 [81,] 1.191816e-08 -2.637431e-09 [82,] 2.196962e-08 1.191816e-08 [83,] 2.265323e-09 2.196962e-08 [84,] 5.123779e-09 2.265323e-09 [85,] 5.954249e-09 5.123779e-09 [86,] 1.282746e-08 5.954249e-09 [87,] -8.261983e-09 1.282746e-08 [88,] 2.472822e-10 -8.261983e-09 [89,] 3.653507e-09 2.472822e-10 [90,] 3.092123e-09 3.653507e-09 [91,] 1.913903e-10 3.092123e-09 [92,] -5.040097e-09 1.913903e-10 [93,] -1.134230e-08 -5.040097e-09 [94,] -7.586712e-10 -1.134230e-08 [95,] 9.449693e-09 -7.586712e-10 [96,] 1.910949e-09 9.449693e-09 [97,] -5.555003e-09 1.910949e-09 [98,] 2.935931e-10 -5.555003e-09 [99,] -8.116539e-10 2.935931e-10 [100,] -1.730608e-09 -8.116539e-10 [101,] 2.976905e-10 -1.730608e-09 [102,] 5.663588e-10 2.976905e-10 [103,] -3.581396e-09 5.663588e-10 [104,] -7.113432e-09 -3.581396e-09 [105,] -1.361006e-08 -7.113432e-09 [106,] 6.556555e-09 -1.361006e-08 [107,] 7.165935e-09 6.556555e-09 [108,] -2.183001e-08 7.165935e-09 [109,] 1.684860e-09 -2.183001e-08 [110,] 7.172029e-09 1.684860e-09 [111,] -3.551862e-09 7.172029e-09 [112,] -1.445504e-08 -3.551862e-09 [113,] -2.262527e-08 -1.445504e-08 [114,] -2.463934e-09 -2.262527e-08 [115,] -6.079434e-09 -2.463934e-09 [116,] -1.396753e-10 -6.079434e-09 [117,] -2.612002e-08 -1.396753e-10 [118,] 3.840122e-09 -2.612002e-08 [119,] -1.553859e-08 3.840122e-09 [120,] -3.378005e-08 -1.553859e-08 [121,] -7.655050e-10 -3.378005e-08 [122,] -2.613607e-08 -7.655050e-10 [123,] -6.077702e-09 -2.613607e-08 [124,] 1.590332e-09 -6.077702e-09 [125,] -4.384753e-09 1.590332e-09 [126,] -3.406845e-08 -4.384753e-09 [127,] -8.263837e-09 -3.406845e-08 [128,] -3.665420e-09 -8.263837e-09 [129,] -3.851876e-08 -3.665420e-09 [130,] 1.457278e-09 -3.851876e-08 [131,] -2.783805e-08 1.457278e-09 [132,] -5.710233e-09 -2.783805e-08 [133,] -2.949895e-09 -5.710233e-09 [134,] 3.362692e-09 -2.949895e-09 [135,] -8.194687e-09 3.362692e-09 [136,] 4.815177e-10 -8.194687e-09 [137,] -7.263926e-09 4.815177e-10 [138,] -6.717435e-09 -7.263926e-09 [139,] -1.077389e-08 -6.717435e-09 [140,] -4.798097e-09 -1.077389e-08 [141,] -1.172763e-08 -4.798097e-09 [142,] -3.995278e-08 -1.172763e-08 [143,] -3.929975e-08 -3.995278e-08 [144,] 4.253027e-08 -3.929975e-08 [145,] -5.852915e-09 4.253027e-08 [146,] -2.982267e-10 -5.852915e-09 [147,] -1.088724e-08 -2.982267e-10 [148,] -2.310356e-09 -1.088724e-08 [149,] -9.237841e-09 -2.310356e-09 [150,] 4.004591e-08 -9.237841e-09 [151,] -1.312483e-08 4.004591e-08 [152,] -7.844214e-09 -1.312483e-08 [153,] 3.531368e-08 -7.844214e-09 [154,] -2.990728e-09 3.531368e-08 [155,] 4.903607e-08 -2.990728e-09 [156,] 3.008395e-08 4.903607e-08 [157,] -8.319161e-09 3.008395e-08 [158,] 5.254581e-10 -8.319161e-09 [159,] -1.325027e-08 5.254581e-10 [160,] -1.689410e-09 -1.325027e-08 [161,] 2.755725e-08 -1.689410e-09 [162,] -1.186442e-08 2.755725e-08 [163,] 2.366629e-08 -1.186442e-08 [164,] -1.001670e-08 2.366629e-08 [165,] 2.314532e-08 -1.001670e-08 [166,] -6.024919e-09 2.314532e-08 [167,] -4.883586e-09 -6.024919e-09 [168,] -1.258494e-08 -4.883586e-09 [169,] 2.315130e-08 -1.258494e-08 [170,] 4.002466e-10 2.315130e-08 [171,] -1.253815e-08 4.002466e-10 [172,] -1.762995e-09 -1.253815e-08 [173,] 1.940102e-08 -1.762995e-09 [174,] -1.068786e-08 1.940102e-08 [175,] 1.576027e-08 -1.068786e-08 [176,] 2.057624e-08 1.576027e-08 [177,] -1.548356e-08 2.057624e-08 [178,] 2.594977e-08 -1.548356e-08 [179,] 2.729383e-08 2.594977e-08 [180,] -1.211112e-08 2.729383e-08 [181,] -9.795453e-09 -1.211112e-08 [182,] -4.371815e-09 -9.795453e-09 [183,] -1.482576e-08 -4.371815e-09 [184,] -6.523110e-09 -1.482576e-08 [185,] -1.354976e-08 -6.523110e-09 [186,] -1.339632e-08 -1.354976e-08 [187,] -1.733337e-08 -1.339632e-08 [188,] 7.990811e-09 -1.733337e-08 [189,] 1.649192e-09 7.990811e-09 [190,] -7.576603e-09 1.649192e-09 [191,] -2.216798e-09 -7.576603e-09 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -5.836723e-09 -8.094662e-09 2 5.543537e-11 -5.836723e-09 3 -1.059642e-08 5.543537e-11 4 -2.532605e-09 -1.059642e-08 5 -9.523272e-09 -2.532605e-09 6 -9.414170e-09 -9.523272e-09 7 -1.338654e-08 -9.414170e-09 8 -7.223964e-09 -1.338654e-08 9 -1.333926e-08 -7.223964e-09 10 6.096096e-09 -1.333926e-08 11 -2.424756e-09 6.096096e-09 12 9.123620e-09 -2.424756e-09 13 -1.937498e-08 9.123620e-09 14 1.270383e-08 -1.937498e-08 15 6.198129e-09 1.270383e-08 16 -1.482399e-08 6.198129e-09 17 -2.207696e-08 -1.482399e-08 18 7.091596e-09 -2.207696e-08 19 3.420478e-09 7.091596e-09 20 -2.029817e-08 3.420478e-09 21 2.732710e-09 -2.029817e-08 22 1.322114e-08 2.732710e-09 23 -1.625306e-08 1.322114e-08 24 -3.449853e-08 -1.625306e-08 25 8.543845e-09 -3.449853e-08 26 1.128128e-08 8.543845e-09 27 3.422160e-09 1.128128e-08 28 1.174477e-08 3.422160e-09 29 4.507621e-09 1.174477e-08 30 4.613464e-09 4.507621e-09 31 -3.959767e-08 4.613464e-09 32 -3.241888e-08 -3.959767e-08 33 2.783303e-10 -3.241888e-08 34 1.073880e-08 2.783303e-10 35 1.236481e-08 1.073880e-08 36 -4.721491e-08 1.236481e-08 37 -4.442280e-08 -4.721491e-08 38 -3.880062e-08 -4.442280e-08 39 1.118771e-09 -3.880062e-08 40 -4.145219e-08 1.118771e-09 41 -4.843513e-08 -4.145219e-08 42 -4.857950e-08 -4.843513e-08 43 -1.174581e-09 -4.857950e-08 44 3.431793e-09 -1.174581e-09 45 -2.176002e-09 3.431793e-09 46 -4.243028e-08 -2.176002e-09 47 -4.198759e-08 -4.243028e-08 48 4.019968e-08 -4.198759e-08 49 4.228494e-08 4.019968e-08 50 9.309018e-09 4.228494e-08 51 3.712360e-08 9.309018e-09 52 4.592267e-08 3.712360e-08 53 3.920573e-08 4.592267e-08 54 3.871591e-08 3.920573e-08 55 3.542212e-08 3.871591e-08 56 4.069877e-08 3.542212e-08 57 3.489312e-08 4.069877e-08 58 6.159635e-09 3.489312e-08 59 7.495692e-09 6.159635e-09 60 2.962354e-08 7.495692e-09 61 1.593709e-09 2.962354e-08 62 7.303306e-09 1.593709e-09 63 2.682547e-08 7.303306e-09 64 4.484874e-09 2.682547e-08 65 2.674752e-08 4.484874e-09 66 2.712326e-08 2.674752e-08 67 2.300350e-08 2.712326e-08 68 2.849846e-08 2.300350e-08 69 2.238708e-08 2.849846e-08 70 3.744966e-09 2.238708e-08 71 3.537082e-08 3.744966e-09 72 1.722867e-08 3.537082e-08 73 1.965954e-08 1.722867e-08 74 4.372377e-09 1.965954e-08 75 1.430760e-08 4.372377e-09 76 2.280885e-08 1.430760e-08 77 1.572657e-08 2.280885e-08 78 1.594347e-08 1.572657e-08 79 1.185149e-08 1.594347e-08 80 -2.637431e-09 1.185149e-08 81 1.191816e-08 -2.637431e-09 82 2.196962e-08 1.191816e-08 83 2.265323e-09 2.196962e-08 84 5.123779e-09 2.265323e-09 85 5.954249e-09 5.123779e-09 86 1.282746e-08 5.954249e-09 87 -8.261983e-09 1.282746e-08 88 2.472822e-10 -8.261983e-09 89 3.653507e-09 2.472822e-10 90 3.092123e-09 3.653507e-09 91 1.913903e-10 3.092123e-09 92 -5.040097e-09 1.913903e-10 93 -1.134230e-08 -5.040097e-09 94 -7.586712e-10 -1.134230e-08 95 9.449693e-09 -7.586712e-10 96 1.910949e-09 9.449693e-09 97 -5.555003e-09 1.910949e-09 98 2.935931e-10 -5.555003e-09 99 -8.116539e-10 2.935931e-10 100 -1.730608e-09 -8.116539e-10 101 2.976905e-10 -1.730608e-09 102 5.663588e-10 2.976905e-10 103 -3.581396e-09 5.663588e-10 104 -7.113432e-09 -3.581396e-09 105 -1.361006e-08 -7.113432e-09 106 6.556555e-09 -1.361006e-08 107 7.165935e-09 6.556555e-09 108 -2.183001e-08 7.165935e-09 109 1.684860e-09 -2.183001e-08 110 7.172029e-09 1.684860e-09 111 -3.551862e-09 7.172029e-09 112 -1.445504e-08 -3.551862e-09 113 -2.262527e-08 -1.445504e-08 114 -2.463934e-09 -2.262527e-08 115 -6.079434e-09 -2.463934e-09 116 -1.396753e-10 -6.079434e-09 117 -2.612002e-08 -1.396753e-10 118 3.840122e-09 -2.612002e-08 119 -1.553859e-08 3.840122e-09 120 -3.378005e-08 -1.553859e-08 121 -7.655050e-10 -3.378005e-08 122 -2.613607e-08 -7.655050e-10 123 -6.077702e-09 -2.613607e-08 124 1.590332e-09 -6.077702e-09 125 -4.384753e-09 1.590332e-09 126 -3.406845e-08 -4.384753e-09 127 -8.263837e-09 -3.406845e-08 128 -3.665420e-09 -8.263837e-09 129 -3.851876e-08 -3.665420e-09 130 1.457278e-09 -3.851876e-08 131 -2.783805e-08 1.457278e-09 132 -5.710233e-09 -2.783805e-08 133 -2.949895e-09 -5.710233e-09 134 3.362692e-09 -2.949895e-09 135 -8.194687e-09 3.362692e-09 136 4.815177e-10 -8.194687e-09 137 -7.263926e-09 4.815177e-10 138 -6.717435e-09 -7.263926e-09 139 -1.077389e-08 -6.717435e-09 140 -4.798097e-09 -1.077389e-08 141 -1.172763e-08 -4.798097e-09 142 -3.995278e-08 -1.172763e-08 143 -3.929975e-08 -3.995278e-08 144 4.253027e-08 -3.929975e-08 145 -5.852915e-09 4.253027e-08 146 -2.982267e-10 -5.852915e-09 147 -1.088724e-08 -2.982267e-10 148 -2.310356e-09 -1.088724e-08 149 -9.237841e-09 -2.310356e-09 150 4.004591e-08 -9.237841e-09 151 -1.312483e-08 4.004591e-08 152 -7.844214e-09 -1.312483e-08 153 3.531368e-08 -7.844214e-09 154 -2.990728e-09 3.531368e-08 155 4.903607e-08 -2.990728e-09 156 3.008395e-08 4.903607e-08 157 -8.319161e-09 3.008395e-08 158 5.254581e-10 -8.319161e-09 159 -1.325027e-08 5.254581e-10 160 -1.689410e-09 -1.325027e-08 161 2.755725e-08 -1.689410e-09 162 -1.186442e-08 2.755725e-08 163 2.366629e-08 -1.186442e-08 164 -1.001670e-08 2.366629e-08 165 2.314532e-08 -1.001670e-08 166 -6.024919e-09 2.314532e-08 167 -4.883586e-09 -6.024919e-09 168 -1.258494e-08 -4.883586e-09 169 2.315130e-08 -1.258494e-08 170 4.002466e-10 2.315130e-08 171 -1.253815e-08 4.002466e-10 172 -1.762995e-09 -1.253815e-08 173 1.940102e-08 -1.762995e-09 174 -1.068786e-08 1.940102e-08 175 1.576027e-08 -1.068786e-08 176 2.057624e-08 1.576027e-08 177 -1.548356e-08 2.057624e-08 178 2.594977e-08 -1.548356e-08 179 2.729383e-08 2.594977e-08 180 -1.211112e-08 2.729383e-08 181 -9.795453e-09 -1.211112e-08 182 -4.371815e-09 -9.795453e-09 183 -1.482576e-08 -4.371815e-09 184 -6.523110e-09 -1.482576e-08 185 -1.354976e-08 -6.523110e-09 186 -1.339632e-08 -1.354976e-08 187 -1.733337e-08 -1.339632e-08 188 7.990811e-09 -1.733337e-08 189 1.649192e-09 7.990811e-09 190 -7.576603e-09 1.649192e-09 191 -2.216798e-09 -7.576603e-09 > 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/freestat/rcomp/tmp/74vy51227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8p0pj1227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/93m6t1227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10k6d71227834072.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/11sgjp1227834072.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/freestat/rcomp/tmp/12t5kv1227834072.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/freestat/rcomp/tmp/13mvi61227834072.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/freestat/rcomp/tmp/14r2uz1227834072.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/15juru1227834072.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/167nr61227834072.tab") + } > > system("convert tmp/1dl2t1227834072.ps tmp/1dl2t1227834072.png") > system("convert tmp/2xqu91227834072.ps tmp/2xqu91227834072.png") > system("convert tmp/3w0k41227834072.ps tmp/3w0k41227834072.png") > system("convert tmp/4qd7g1227834072.ps tmp/4qd7g1227834072.png") > system("convert tmp/5bczt1227834072.ps tmp/5bczt1227834072.png") > system("convert tmp/6ejrg1227834072.ps tmp/6ejrg1227834072.png") > system("convert tmp/74vy51227834072.ps tmp/74vy51227834072.png") > system("convert tmp/8p0pj1227834072.ps tmp/8p0pj1227834072.png") > system("convert tmp/93m6t1227834072.ps tmp/93m6t1227834072.png") > system("convert tmp/10k6d71227834072.ps tmp/10k6d71227834072.png") > > > proc.time() user system elapsed 6.318 2.735 6.778