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Type 'q()' to quit R. > x <- array(list(1687 + ,0 + ,NA + ,1508 + ,0 + ,1687 + ,1507 + ,0 + ,1508 + ,1385 + ,0 + ,1507 + ,1632 + ,0 + ,1385 + ,1511 + ,0 + ,1632 + ,1559 + ,0 + ,1511 + ,1630 + ,0 + ,1559 + ,1579 + ,0 + ,1630 + ,1653 + ,0 + ,1579 + ,2152 + ,0 + ,1653 + ,2148 + ,0 + ,2152 + ,1752 + ,0 + ,2148 + ,1765 + ,0 + ,1752 + ,1717 + ,0 + ,1765 + ,1558 + ,0 + ,1717 + ,1575 + ,0 + ,1558 + ,1520 + ,0 + ,1575 + ,1805 + ,0 + ,1520 + ,1800 + ,0 + ,1805 + ,1719 + ,0 + ,1800 + ,2008 + ,0 + ,1719 + ,2242 + ,0 + ,2008 + ,2478 + ,0 + ,2242 + ,2030 + ,0 + ,2478 + ,1655 + ,0 + ,2030 + ,1693 + ,0 + ,1655 + ,1623 + ,0 + ,1693 + ,1805 + ,0 + ,1623 + ,1746 + ,0 + ,1805 + ,1795 + ,0 + ,1746 + ,1926 + ,0 + ,1795 + ,1619 + ,0 + ,1926 + ,1992 + ,0 + ,1619 + ,2233 + ,0 + ,1992 + ,2192 + ,0 + ,2233 + ,2080 + ,0 + ,2192 + ,1768 + ,0 + ,2080 + ,1835 + ,0 + ,1768 + ,1569 + ,0 + ,1835 + ,1976 + ,0 + ,1569 + ,1853 + ,0 + ,1976 + ,1965 + ,0 + ,1853 + ,1689 + ,0 + ,1965 + ,1778 + ,0 + ,1689 + ,1976 + ,0 + ,1778 + ,2397 + ,0 + ,1976 + ,2654 + ,0 + ,2397 + ,2097 + ,0 + ,2654 + ,1963 + ,0 + ,2097 + ,1677 + ,0 + ,1963 + ,1941 + ,0 + ,1677 + ,2003 + ,0 + ,1941 + ,1813 + ,0 + ,2003 + ,2012 + ,0 + ,1813 + ,1912 + ,0 + ,2012 + ,2084 + ,0 + ,1912 + ,2080 + ,0 + ,2084 + ,2118 + ,0 + ,2080 + ,2150 + ,0 + ,2118 + ,1608 + ,0 + ,2150 + ,1503 + ,0 + ,1608 + ,1548 + ,0 + ,1503 + ,1382 + ,0 + ,1548 + ,1731 + ,0 + ,1382 + ,1798 + ,0 + ,1731 + ,1779 + ,0 + ,1798 + ,1887 + ,0 + ,1779 + ,2004 + ,0 + ,1887 + ,2077 + ,0 + ,2004 + ,2092 + ,0 + ,2077 + ,2051 + ,0 + ,2092 + ,1577 + ,0 + ,2051 + ,1356 + ,0 + ,1577 + ,1652 + ,0 + ,1356 + ,1382 + ,0 + ,1652 + ,1519 + ,0 + ,1382 + ,1421 + ,0 + ,1519 + ,1442 + ,0 + ,1421 + ,1543 + ,0 + ,1442 + ,1656 + ,0 + ,1543 + ,1561 + ,0 + ,1656 + ,1905 + ,0 + ,1561 + ,2199 + ,0 + ,1905 + ,1473 + ,0 + ,2199 + ,1655 + ,0 + ,1473 + ,1407 + ,0 + ,1655 + ,1395 + ,0 + ,1407 + ,1530 + ,0 + ,1395 + ,1309 + ,0 + ,1530 + ,1526 + ,0 + ,1309 + ,1327 + ,0 + ,1526 + ,1627 + ,0 + ,1327 + ,1748 + ,0 + ,1627 + ,1958 + ,0 + ,1748 + ,2274 + ,0 + ,1958 + ,1648 + ,0 + ,2274 + ,1401 + ,0 + ,1648 + ,1411 + ,0 + ,1401 + ,1403 + ,0 + ,1411 + ,1394 + ,0 + ,1403 + ,1520 + ,0 + ,1394 + ,1528 + ,0 + ,1520 + ,1643 + ,0 + ,1528 + ,1515 + ,0 + ,1643 + ,1685 + ,0 + ,1515 + ,2000 + ,0 + ,1685 + ,2215 + ,0 + ,2000 + ,1956 + ,0 + ,2215 + ,1462 + ,0 + ,1956 + ,1563 + ,0 + ,1462 + ,1459 + ,0 + ,1563 + ,1446 + ,0 + ,1459 + ,1622 + ,0 + ,1446 + ,1657 + ,0 + ,1622 + ,1638 + ,0 + ,1657 + ,1643 + ,0 + ,1638 + ,1683 + ,0 + ,1643 + ,2050 + ,0 + ,1683 + ,2262 + ,0 + ,2050 + ,1813 + ,0 + ,2262 + ,1445 + ,0 + ,1813 + ,1762 + ,0 + ,1445 + ,1461 + ,0 + ,1762 + ,1556 + ,0 + ,1461 + ,1431 + ,0 + ,1556 + ,1427 + ,0 + ,1431 + ,1554 + ,0 + ,1427 + ,1645 + ,0 + ,1554 + ,1653 + ,0 + ,1645 + ,2016 + ,0 + ,1653 + ,2207 + ,0 + ,2016 + ,1665 + ,0 + ,2207 + ,1361 + ,0 + ,1665 + ,1506 + ,0 + ,1361 + ,1360 + ,0 + ,1506 + ,1453 + ,0 + ,1360 + ,1522 + ,0 + ,1453 + ,1460 + ,0 + ,1522 + ,1552 + ,0 + ,1460 + ,1548 + ,0 + ,1552 + ,1827 + ,0 + ,1548 + ,1737 + ,0 + ,1827 + ,1941 + ,0 + ,1737 + ,1474 + ,0 + ,1941 + ,1458 + ,0 + ,1474 + ,1542 + ,0 + ,1458 + ,1404 + ,0 + ,1542 + ,1522 + ,0 + ,1404 + ,1385 + ,0 + ,1522 + ,1641 + ,0 + ,1385 + ,1510 + ,0 + ,1641 + ,1681 + ,0 + ,1510 + ,1938 + ,0 + ,1681 + ,1868 + ,0 + ,1938 + ,1726 + ,0 + ,1868 + ,1456 + ,0 + ,1726 + ,1445 + ,0 + ,1456 + ,1456 + ,0 + ,1445 + ,1365 + ,0 + ,1456 + ,1487 + ,0 + ,1365 + ,1558 + ,0 + ,1487 + ,1488 + ,0 + ,1558 + ,1684 + ,0 + ,1488 + ,1594 + ,0 + ,1684 + ,1850 + ,0 + ,1594 + ,1998 + ,0 + ,1850 + ,2079 + ,0 + ,1998 + ,1494 + ,0 + ,2079 + ,1057 + ,1 + ,1494 + ,1218 + ,1 + ,1057 + ,1168 + ,1 + ,1218 + ,1236 + ,1 + ,1168 + ,1076 + ,1 + ,1236 + ,1174 + ,1 + ,1076 + ,1139 + ,1 + ,1174 + ,1427 + ,1 + ,1139 + ,1487 + ,1 + ,1427 + ,1483 + ,1 + ,1487 + ,1513 + ,1 + ,1483 + ,1357 + ,1 + ,1513 + ,1165 + ,1 + ,1357 + ,1282 + ,1 + ,1165 + ,1110 + ,1 + ,1282 + ,1297 + ,1 + ,1110 + ,1185 + ,1 + ,1297 + ,1222 + ,1 + ,1185 + ,1284 + ,1 + ,1222 + ,1444 + ,1 + ,1284 + ,1575 + ,1 + ,1444 + ,1737 + ,1 + ,1575 + ,1763 + ,1 + ,1737) + ,dim=c(3 + ,192) + ,dimnames=list(c('Accidents' + ,'Belt' + ,'A1') + ,1:192)) > y <- array(NA,dim=c(3,192),dimnames=list(c('Accidents','Belt','A1'),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' > par3 <- 'Linear Trend' > par2 <- 'Include Monthly Dummies' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 () > #Author: root > #To cite this work: Wessa P., (2013), Multiple Regression (v1.0.29) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, 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 Accidents Belt A1 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 1687 0 NA 1 0 0 0 0 0 0 0 0 0 0 1 2 1508 0 1687 0 1 0 0 0 0 0 0 0 0 0 2 3 1507 0 1508 0 0 1 0 0 0 0 0 0 0 0 3 4 1385 0 1507 0 0 0 1 0 0 0 0 0 0 0 4 5 1632 0 1385 0 0 0 0 1 0 0 0 0 0 0 5 6 1511 0 1632 0 0 0 0 0 1 0 0 0 0 0 6 7 1559 0 1511 0 0 0 0 0 0 1 0 0 0 0 7 8 1630 0 1559 0 0 0 0 0 0 0 1 0 0 0 8 9 1579 0 1630 0 0 0 0 0 0 0 0 1 0 0 9 10 1653 0 1579 0 0 0 0 0 0 0 0 0 1 0 10 11 2152 0 1653 0 0 0 0 0 0 0 0 0 0 1 11 12 2148 0 2152 0 0 0 0 0 0 0 0 0 0 0 12 13 1752 0 2148 1 0 0 0 0 0 0 0 0 0 0 13 14 1765 0 1752 0 1 0 0 0 0 0 0 0 0 0 14 15 1717 0 1765 0 0 1 0 0 0 0 0 0 0 0 15 16 1558 0 1717 0 0 0 1 0 0 0 0 0 0 0 16 17 1575 0 1558 0 0 0 0 1 0 0 0 0 0 0 17 18 1520 0 1575 0 0 0 0 0 1 0 0 0 0 0 18 19 1805 0 1520 0 0 0 0 0 0 1 0 0 0 0 19 20 1800 0 1805 0 0 0 0 0 0 0 1 0 0 0 20 21 1719 0 1800 0 0 0 0 0 0 0 0 1 0 0 21 22 2008 0 1719 0 0 0 0 0 0 0 0 0 1 0 22 23 2242 0 2008 0 0 0 0 0 0 0 0 0 0 1 23 24 2478 0 2242 0 0 0 0 0 0 0 0 0 0 0 24 25 2030 0 2478 1 0 0 0 0 0 0 0 0 0 0 25 26 1655 0 2030 0 1 0 0 0 0 0 0 0 0 0 26 27 1693 0 1655 0 0 1 0 0 0 0 0 0 0 0 27 28 1623 0 1693 0 0 0 1 0 0 0 0 0 0 0 28 29 1805 0 1623 0 0 0 0 1 0 0 0 0 0 0 29 30 1746 0 1805 0 0 0 0 0 1 0 0 0 0 0 30 31 1795 0 1746 0 0 0 0 0 0 1 0 0 0 0 31 32 1926 0 1795 0 0 0 0 0 0 0 1 0 0 0 32 33 1619 0 1926 0 0 0 0 0 0 0 0 1 0 0 33 34 1992 0 1619 0 0 0 0 0 0 0 0 0 1 0 34 35 2233 0 1992 0 0 0 0 0 0 0 0 0 0 1 35 36 2192 0 2233 0 0 0 0 0 0 0 0 0 0 0 36 37 2080 0 2192 1 0 0 0 0 0 0 0 0 0 0 37 38 1768 0 2080 0 1 0 0 0 0 0 0 0 0 0 38 39 1835 0 1768 0 0 1 0 0 0 0 0 0 0 0 39 40 1569 0 1835 0 0 0 1 0 0 0 0 0 0 0 40 41 1976 0 1569 0 0 0 0 1 0 0 0 0 0 0 41 42 1853 0 1976 0 0 0 0 0 1 0 0 0 0 0 42 43 1965 0 1853 0 0 0 0 0 0 1 0 0 0 0 43 44 1689 0 1965 0 0 0 0 0 0 0 1 0 0 0 44 45 1778 0 1689 0 0 0 0 0 0 0 0 1 0 0 45 46 1976 0 1778 0 0 0 0 0 0 0 0 0 1 0 46 47 2397 0 1976 0 0 0 0 0 0 0 0 0 0 1 47 48 2654 0 2397 0 0 0 0 0 0 0 0 0 0 0 48 49 2097 0 2654 1 0 0 0 0 0 0 0 0 0 0 49 50 1963 0 2097 0 1 0 0 0 0 0 0 0 0 0 50 51 1677 0 1963 0 0 1 0 0 0 0 0 0 0 0 51 52 1941 0 1677 0 0 0 1 0 0 0 0 0 0 0 52 53 2003 0 1941 0 0 0 0 1 0 0 0 0 0 0 53 54 1813 0 2003 0 0 0 0 0 1 0 0 0 0 0 54 55 2012 0 1813 0 0 0 0 0 0 1 0 0 0 0 55 56 1912 0 2012 0 0 0 0 0 0 0 1 0 0 0 56 57 2084 0 1912 0 0 0 0 0 0 0 0 1 0 0 57 58 2080 0 2084 0 0 0 0 0 0 0 0 0 1 0 58 59 2118 0 2080 0 0 0 0 0 0 0 0 0 0 1 59 60 2150 0 2118 0 0 0 0 0 0 0 0 0 0 0 60 61 1608 0 2150 1 0 0 0 0 0 0 0 0 0 0 61 62 1503 0 1608 0 1 0 0 0 0 0 0 0 0 0 62 63 1548 0 1503 0 0 1 0 0 0 0 0 0 0 0 63 64 1382 0 1548 0 0 0 1 0 0 0 0 0 0 0 64 65 1731 0 1382 0 0 0 0 1 0 0 0 0 0 0 65 66 1798 0 1731 0 0 0 0 0 1 0 0 0 0 0 66 67 1779 0 1798 0 0 0 0 0 0 1 0 0 0 0 67 68 1887 0 1779 0 0 0 0 0 0 0 1 0 0 0 68 69 2004 0 1887 0 0 0 0 0 0 0 0 1 0 0 69 70 2077 0 2004 0 0 0 0 0 0 0 0 0 1 0 70 71 2092 0 2077 0 0 0 0 0 0 0 0 0 0 1 71 72 2051 0 2092 0 0 0 0 0 0 0 0 0 0 0 72 73 1577 0 2051 1 0 0 0 0 0 0 0 0 0 0 73 74 1356 0 1577 0 1 0 0 0 0 0 0 0 0 0 74 75 1652 0 1356 0 0 1 0 0 0 0 0 0 0 0 75 76 1382 0 1652 0 0 0 1 0 0 0 0 0 0 0 76 77 1519 0 1382 0 0 0 0 1 0 0 0 0 0 0 77 78 1421 0 1519 0 0 0 0 0 1 0 0 0 0 0 78 79 1442 0 1421 0 0 0 0 0 0 1 0 0 0 0 79 80 1543 0 1442 0 0 0 0 0 0 0 1 0 0 0 80 81 1656 0 1543 0 0 0 0 0 0 0 0 1 0 0 81 82 1561 0 1656 0 0 0 0 0 0 0 0 0 1 0 82 83 1905 0 1561 0 0 0 0 0 0 0 0 0 0 1 83 84 2199 0 1905 0 0 0 0 0 0 0 0 0 0 0 84 85 1473 0 2199 1 0 0 0 0 0 0 0 0 0 0 85 86 1655 0 1473 0 1 0 0 0 0 0 0 0 0 0 86 87 1407 0 1655 0 0 1 0 0 0 0 0 0 0 0 87 88 1395 0 1407 0 0 0 1 0 0 0 0 0 0 0 88 89 1530 0 1395 0 0 0 0 1 0 0 0 0 0 0 89 90 1309 0 1530 0 0 0 0 0 1 0 0 0 0 0 90 91 1526 0 1309 0 0 0 0 0 0 1 0 0 0 0 91 92 1327 0 1526 0 0 0 0 0 0 0 1 0 0 0 92 93 1627 0 1327 0 0 0 0 0 0 0 0 1 0 0 93 94 1748 0 1627 0 0 0 0 0 0 0 0 0 1 0 94 95 1958 0 1748 0 0 0 0 0 0 0 0 0 0 1 95 96 2274 0 1958 0 0 0 0 0 0 0 0 0 0 0 96 97 1648 0 2274 1 0 0 0 0 0 0 0 0 0 0 97 98 1401 0 1648 0 1 0 0 0 0 0 0 0 0 0 98 99 1411 0 1401 0 0 1 0 0 0 0 0 0 0 0 99 100 1403 0 1411 0 0 0 1 0 0 0 0 0 0 0 100 101 1394 0 1403 0 0 0 0 1 0 0 0 0 0 0 101 102 1520 0 1394 0 0 0 0 0 1 0 0 0 0 0 102 103 1528 0 1520 0 0 0 0 0 0 1 0 0 0 0 103 104 1643 0 1528 0 0 0 0 0 0 0 1 0 0 0 104 105 1515 0 1643 0 0 0 0 0 0 0 0 1 0 0 105 106 1685 0 1515 0 0 0 0 0 0 0 0 0 1 0 106 107 2000 0 1685 0 0 0 0 0 0 0 0 0 0 1 107 108 2215 0 2000 0 0 0 0 0 0 0 0 0 0 0 108 109 1956 0 2215 1 0 0 0 0 0 0 0 0 0 0 109 110 1462 0 1956 0 1 0 0 0 0 0 0 0 0 0 110 111 1563 0 1462 0 0 1 0 0 0 0 0 0 0 0 111 112 1459 0 1563 0 0 0 1 0 0 0 0 0 0 0 112 113 1446 0 1459 0 0 0 0 1 0 0 0 0 0 0 113 114 1622 0 1446 0 0 0 0 0 1 0 0 0 0 0 114 115 1657 0 1622 0 0 0 0 0 0 1 0 0 0 0 115 116 1638 0 1657 0 0 0 0 0 0 0 1 0 0 0 116 117 1643 0 1638 0 0 0 0 0 0 0 0 1 0 0 117 118 1683 0 1643 0 0 0 0 0 0 0 0 0 1 0 118 119 2050 0 1683 0 0 0 0 0 0 0 0 0 0 1 119 120 2262 0 2050 0 0 0 0 0 0 0 0 0 0 0 120 121 1813 0 2262 1 0 0 0 0 0 0 0 0 0 0 121 122 1445 0 1813 0 1 0 0 0 0 0 0 0 0 0 122 123 1762 0 1445 0 0 1 0 0 0 0 0 0 0 0 123 124 1461 0 1762 0 0 0 1 0 0 0 0 0 0 0 124 125 1556 0 1461 0 0 0 0 1 0 0 0 0 0 0 125 126 1431 0 1556 0 0 0 0 0 1 0 0 0 0 0 126 127 1427 0 1431 0 0 0 0 0 0 1 0 0 0 0 127 128 1554 0 1427 0 0 0 0 0 0 0 1 0 0 0 128 129 1645 0 1554 0 0 0 0 0 0 0 0 1 0 0 129 130 1653 0 1645 0 0 0 0 0 0 0 0 0 1 0 130 131 2016 0 1653 0 0 0 0 0 0 0 0 0 0 1 131 132 2207 0 2016 0 0 0 0 0 0 0 0 0 0 0 132 133 1665 0 2207 1 0 0 0 0 0 0 0 0 0 0 133 134 1361 0 1665 0 1 0 0 0 0 0 0 0 0 0 134 135 1506 0 1361 0 0 1 0 0 0 0 0 0 0 0 135 136 1360 0 1506 0 0 0 1 0 0 0 0 0 0 0 136 137 1453 0 1360 0 0 0 0 1 0 0 0 0 0 0 137 138 1522 0 1453 0 0 0 0 0 1 0 0 0 0 0 138 139 1460 0 1522 0 0 0 0 0 0 1 0 0 0 0 139 140 1552 0 1460 0 0 0 0 0 0 0 1 0 0 0 140 141 1548 0 1552 0 0 0 0 0 0 0 0 1 0 0 141 142 1827 0 1548 0 0 0 0 0 0 0 0 0 1 0 142 143 1737 0 1827 0 0 0 0 0 0 0 0 0 0 1 143 144 1941 0 1737 0 0 0 0 0 0 0 0 0 0 0 144 145 1474 0 1941 1 0 0 0 0 0 0 0 0 0 0 145 146 1458 0 1474 0 1 0 0 0 0 0 0 0 0 0 146 147 1542 0 1458 0 0 1 0 0 0 0 0 0 0 0 147 148 1404 0 1542 0 0 0 1 0 0 0 0 0 0 0 148 149 1522 0 1404 0 0 0 0 1 0 0 0 0 0 0 149 150 1385 0 1522 0 0 0 0 0 1 0 0 0 0 0 150 151 1641 0 1385 0 0 0 0 0 0 1 0 0 0 0 151 152 1510 0 1641 0 0 0 0 0 0 0 1 0 0 0 152 153 1681 0 1510 0 0 0 0 0 0 0 0 1 0 0 153 154 1938 0 1681 0 0 0 0 0 0 0 0 0 1 0 154 155 1868 0 1938 0 0 0 0 0 0 0 0 0 0 1 155 156 1726 0 1868 0 0 0 0 0 0 0 0 0 0 0 156 157 1456 0 1726 1 0 0 0 0 0 0 0 0 0 0 157 158 1445 0 1456 0 1 0 0 0 0 0 0 0 0 0 158 159 1456 0 1445 0 0 1 0 0 0 0 0 0 0 0 159 160 1365 0 1456 0 0 0 1 0 0 0 0 0 0 0 160 161 1487 0 1365 0 0 0 0 1 0 0 0 0 0 0 161 162 1558 0 1487 0 0 0 0 0 1 0 0 0 0 0 162 163 1488 0 1558 0 0 0 0 0 0 1 0 0 0 0 163 164 1684 0 1488 0 0 0 0 0 0 0 1 0 0 0 164 165 1594 0 1684 0 0 0 0 0 0 0 0 1 0 0 165 166 1850 0 1594 0 0 0 0 0 0 0 0 0 1 0 166 167 1998 0 1850 0 0 0 0 0 0 0 0 0 0 1 167 168 2079 0 1998 0 0 0 0 0 0 0 0 0 0 0 168 169 1494 0 2079 1 0 0 0 0 0 0 0 0 0 0 169 170 1057 1 1494 0 1 0 0 0 0 0 0 0 0 0 170 171 1218 1 1057 0 0 1 0 0 0 0 0 0 0 0 171 172 1168 1 1218 0 0 0 1 0 0 0 0 0 0 0 172 173 1236 1 1168 0 0 0 0 1 0 0 0 0 0 0 173 174 1076 1 1236 0 0 0 0 0 1 0 0 0 0 0 174 175 1174 1 1076 0 0 0 0 0 0 1 0 0 0 0 175 176 1139 1 1174 0 0 0 0 0 0 0 1 0 0 0 176 177 1427 1 1139 0 0 0 0 0 0 0 0 1 0 0 177 178 1487 1 1427 0 0 0 0 0 0 0 0 0 1 0 178 179 1483 1 1487 0 0 0 0 0 0 0 0 0 0 1 179 180 1513 1 1483 0 0 0 0 0 0 0 0 0 0 0 180 181 1357 1 1513 1 0 0 0 0 0 0 0 0 0 0 181 182 1165 1 1357 0 1 0 0 0 0 0 0 0 0 0 182 183 1282 1 1165 0 0 1 0 0 0 0 0 0 0 0 183 184 1110 1 1282 0 0 0 1 0 0 0 0 0 0 0 184 185 1297 1 1110 0 0 0 0 1 0 0 0 0 0 0 185 186 1185 1 1297 0 0 0 0 0 1 0 0 0 0 0 186 187 1222 1 1185 0 0 0 0 0 0 1 0 0 0 0 187 188 1284 1 1222 0 0 0 0 0 0 0 1 0 0 0 188 189 1444 1 1284 0 0 0 0 0 0 0 0 1 0 0 189 190 1575 1 1444 0 0 0 0 0 0 0 0 0 1 0 190 191 1737 1 1575 0 0 0 0 0 0 0 0 0 0 1 191 192 1763 1 1737 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) Belt A1 M1 M2 M3 1159.5428 -105.2144 0.5298 -501.8695 -467.0447 -309.6414 M4 M5 M6 M7 M8 M9 -448.7368 -250.5770 -378.1953 -272.1536 -296.4647 -250.6528 M10 M11 t -138.3778 -11.7764 -0.8802 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -285.90 -89.40 0.35 86.31 387.49 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1159.54281 144.76390 8.010 1.51e-13 *** Belt -105.21442 37.58564 -2.799 0.005693 ** A1 0.52980 0.06342 8.354 1.91e-14 *** M1 -501.86951 47.04203 -10.669 < 2e-16 *** M2 -467.04473 49.96892 -9.347 < 2e-16 *** M3 -309.64136 56.23447 -5.506 1.28e-07 *** M4 -448.73680 54.36084 -8.255 3.49e-14 *** M5 -250.57697 58.48815 -4.284 3.01e-05 *** M6 -378.19534 53.42057 -7.080 3.32e-11 *** M7 -272.15357 55.27050 -4.924 1.94e-06 *** M8 -296.46471 52.65887 -5.630 7.01e-08 *** M9 -250.65280 52.13892 -4.807 3.27e-06 *** M10 -138.37779 50.55693 -2.737 0.006835 ** M11 -11.77638 47.40539 -0.248 0.804100 t -0.88023 0.23372 -3.766 0.000226 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 129.1 on 176 degrees of freedom (1 observation deleted due to missingness) Multiple R-squared: 0.8168, Adjusted R-squared: 0.8022 F-statistic: 56.05 on 14 and 176 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,] 0.54271876 0.9145624843 4.572812e-01 [2,] 0.37328770 0.7465754033 6.267123e-01 [3,] 0.24241353 0.4848270602 7.575865e-01 [4,] 0.29617851 0.5923570166 7.038215e-01 [5,] 0.21867850 0.4373570083 7.813215e-01 [6,] 0.21534629 0.4306925822 7.846537e-01 [7,] 0.17125835 0.3425166937 8.287417e-01 [8,] 0.28356543 0.5671308595 7.164346e-01 [9,] 0.25988387 0.5197677486 7.401161e-01 [10,] 0.19246265 0.3849252939 8.075374e-01 [11,] 0.13685996 0.2737199291 8.631400e-01 [12,] 0.09603431 0.1920686106 9.039657e-01 [13,] 0.07444008 0.1488801569 9.255599e-01 [14,] 0.05115691 0.1023138204 9.488431e-01 [15,] 0.10208973 0.2041794692 8.979103e-01 [16,] 0.07266492 0.1453298300 9.273351e-01 [17,] 0.06874605 0.1374921012 9.312539e-01 [18,] 0.13789845 0.2757968913 8.621016e-01 [19,] 0.13206758 0.2641351603 8.679324e-01 [20,] 0.10666313 0.2133262650 8.933369e-01 [21,] 0.07905444 0.1581088775 9.209456e-01 [22,] 0.07991224 0.1598244771 9.200878e-01 [23,] 0.09125888 0.1825177549 9.087411e-01 [24,] 0.07222791 0.1444558173 9.277721e-01 [25,] 0.05708654 0.1141730793 9.429135e-01 [26,] 0.14617019 0.2923403860 8.538298e-01 [27,] 0.11528226 0.2305645161 8.847177e-01 [28,] 0.09588543 0.1917708512 9.041146e-01 [29,] 0.08827278 0.1765455601 9.117272e-01 [30,] 0.13893859 0.2778771808 8.610614e-01 [31,] 0.11779974 0.2355994747 8.822003e-01 [32,] 0.11428346 0.2285669245 8.857165e-01 [33,] 0.17983355 0.3596670986 8.201665e-01 [34,] 0.29536319 0.5907263805 7.046368e-01 [35,] 0.27546023 0.5509204510 7.245398e-01 [36,] 0.24407406 0.4881481297 7.559259e-01 [37,] 0.25486716 0.5097343229 7.451328e-01 [38,] 0.23089433 0.4617886626 7.691057e-01 [39,] 0.30069142 0.6013828361 6.993086e-01 [40,] 0.26890774 0.5378154715 7.310923e-01 [41,] 0.51298463 0.9740307475 4.870154e-01 [42,] 0.76244494 0.4751101235 2.375551e-01 [43,] 0.92544703 0.1491059467 7.455297e-02 [44,] 0.92728373 0.1454325418 7.271627e-02 [45,] 0.91573817 0.1685236642 8.426183e-02 [46,] 0.92615640 0.1476872008 7.384360e-02 [47,] 0.92330726 0.1533854816 7.669274e-02 [48,] 0.93054986 0.1389002841 6.945014e-02 [49,] 0.93367991 0.1326401900 6.632009e-02 [50,] 0.94171365 0.1165726961 5.828635e-02 [51,] 0.95877736 0.0824452863 4.122264e-02 [52,] 0.96438301 0.0712339834 3.561699e-02 [53,] 0.97527484 0.0494503290 2.472516e-02 [54,] 0.97983632 0.0403273608 2.016368e-02 [55,] 0.98109035 0.0378192908 1.890965e-02 [56,] 0.98118251 0.0376349783 1.881749e-02 [57,] 0.98342959 0.0331408191 1.657041e-02 [58,] 0.98463662 0.0307267580 1.536338e-02 [59,] 0.98313029 0.0337394253 1.686971e-02 [60,] 0.98029247 0.0394150562 1.970753e-02 [61,] 0.98073724 0.0385255120 1.926276e-02 [62,] 0.97476249 0.0504750286 2.523751e-02 [63,] 0.96779419 0.0644116204 3.220581e-02 [64,] 0.98518439 0.0296312199 1.481561e-02 [65,] 0.98045714 0.0390857246 1.954286e-02 [66,] 0.98025700 0.0394860047 1.974300e-02 [67,] 0.99091426 0.0181714751 9.085738e-03 [68,] 0.99631717 0.0073656624 3.682831e-03 [69,] 0.99790063 0.0041987492 2.099375e-03 [70,] 0.99705362 0.0058927690 2.946385e-03 [71,] 0.99614761 0.0077047845 3.852392e-03 [72,] 0.99740421 0.0051915875 2.595794e-03 [73,] 0.99639493 0.0072101393 3.605070e-03 [74,] 0.99875928 0.0024814437 1.240722e-03 [75,] 0.99860140 0.0027972012 1.398601e-03 [76,] 0.99812453 0.0037509370 1.875468e-03 [77,] 0.99740555 0.0051888937 2.594447e-03 [78,] 0.99825144 0.0034971289 1.748564e-03 [79,] 0.99796558 0.0040688483 2.034424e-03 [80,] 0.99740045 0.0051990962 2.599548e-03 [81,] 0.99752006 0.0049598795 2.479940e-03 [82,] 0.99657785 0.0068443083 3.422154e-03 [83,] 0.99727366 0.0054526885 2.726344e-03 [84,] 0.99674784 0.0065043282 3.252164e-03 [85,] 0.99579675 0.0084064998 4.203250e-03 [86,] 0.99463845 0.0107230945 5.361547e-03 [87,] 0.99621994 0.0075601157 3.780058e-03 [88,] 0.99586338 0.0082732351 4.136618e-03 [89,] 0.99443657 0.0111268594 5.563430e-03 [90,] 0.99415781 0.0116843767 5.842188e-03 [91,] 0.99816216 0.0036756731 1.837837e-03 [92,] 0.99811548 0.0037690437 1.884522e-03 [93,] 0.99750740 0.0049852050 2.492602e-03 [94,] 0.99646350 0.0070730046 3.536502e-03 [95,] 0.99644824 0.0071035263 3.551763e-03 [96,] 0.99722302 0.0055539668 2.776983e-03 [97,] 0.99654086 0.0069182868 3.459143e-03 [98,] 0.99515608 0.0096878399 4.843920e-03 [99,] 0.99346486 0.0130702718 6.535136e-03 [100,] 0.99401903 0.0119619395 5.980970e-03 [101,] 0.99426200 0.0114760034 5.738002e-03 [102,] 0.99713326 0.0057334866 2.866743e-03 [103,] 0.99819342 0.0036131538 1.806577e-03 [104,] 0.99753460 0.0049308037 2.465402e-03 [105,] 0.99942963 0.0011407476 5.703738e-04 [106,] 0.99922552 0.0015489572 7.744786e-04 [107,] 0.99891321 0.0021735721 1.086786e-03 [108,] 0.99838793 0.0032241333 1.612067e-03 [109,] 0.99788867 0.0042226581 2.111329e-03 [110,] 0.99702814 0.0059437247 2.971862e-03 [111,] 0.99573040 0.0085392044 4.269602e-03 [112,] 0.99674661 0.0065067730 3.253387e-03 [113,] 0.99765061 0.0046987780 2.349389e-03 [114,] 0.99976328 0.0004734327 2.367163e-04 [115,] 0.99992801 0.0001439755 7.198775e-05 [116,] 0.99988127 0.0002374620 1.187310e-04 [117,] 0.99981826 0.0003634798 1.817399e-04 [118,] 0.99969780 0.0006044072 3.022036e-04 [119,] 0.99950575 0.0009885094 4.942547e-04 [120,] 0.99959787 0.0008042614 4.021307e-04 [121,] 0.99938121 0.0012375832 6.187916e-04 [122,] 0.99918517 0.0016296620 8.148310e-04 [123,] 0.99875801 0.0024839775 1.241989e-03 [124,] 0.99827586 0.0034482704 1.724135e-03 [125,] 0.99857298 0.0028540431 1.427022e-03 [126,] 0.99824204 0.0035159111 1.757956e-03 [127,] 0.99724840 0.0055032095 2.751605e-03 [128,] 0.99649140 0.0070171942 3.508597e-03 [129,] 0.99535639 0.0092872247 4.643612e-03 [130,] 0.99315517 0.0136896695 6.844835e-03 [131,] 0.98988692 0.0202261660 1.011308e-02 [132,] 0.98503465 0.0299306974 1.496535e-02 [133,] 0.99323980 0.0135203927 6.760196e-03 [134,] 0.98969979 0.0206004294 1.030021e-02 [135,] 0.98687360 0.0262528071 1.312640e-02 [136,] 0.99432337 0.0113532656 5.676633e-03 [137,] 0.99250179 0.0149964246 7.498212e-03 [138,] 0.99541723 0.0091655391 4.582770e-03 [139,] 0.99330794 0.0133841251 6.692063e-03 [140,] 0.98906558 0.0218688371 1.093442e-02 [141,] 0.98592165 0.0281566998 1.407835e-02 [142,] 0.98341321 0.0331735888 1.658679e-02 [143,] 0.98351449 0.0329710221 1.648551e-02 [144,] 0.97636596 0.0472680786 2.363404e-02 [145,] 0.96152005 0.0769598968 3.847995e-02 [146,] 0.96846582 0.0630683629 3.153418e-02 [147,] 0.96888676 0.0622264769 3.111324e-02 [148,] 0.94897510 0.1020497960 5.102490e-02 [149,] 0.92534860 0.1493028050 7.465140e-02 [150,] 0.98572881 0.0285423716 1.427119e-02 [151,] 0.97040739 0.0591852279 2.959261e-02 [152,] 0.95191337 0.0961732628 4.808663e-02 [153,] 0.91452378 0.1709524399 8.547622e-02 [154,] 0.93356688 0.1328662496 6.643312e-02 [155,] 0.85851086 0.2829782779 1.414891e-01 [156,] 0.72503898 0.5499220462 2.749610e-01 [157,] 0.58535222 0.8292955614 4.146478e-01 > postscript(file="/var/wessaorg/rcomp/tmp/1rypm1383550854.ps",horizontal=F,onefile=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$resid) Warning message: In x[, 1] - mysum$resid : longer object length is not a multiple of shorter object length > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2hf0c1383550854.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3bph21383550854.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4axfo1383550854.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5bmts1383550854.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 191 Frequency = 1 2 3 4 5 6 7 -76.5156196 -139.2039870 -120.6985092 -6.3421184 -129.7049076 -122.7602484 8 9 10 11 12 13 -51.9994348 -185.5471398 -195.9219444 138.1514402 -141.1165074 -32.2475463 14 15 16 17 18 19 156.6099772 -54.8006057 -48.3943772 -144.4352678 -79.9433196 129.0343280 20 21 22 23 24 25 -1.7682183 -125.0508796 95.4684120 50.6341072 151.7640093 81.4802009 26 27 28 29 30 31 -90.1125089 -9.9594478 39.8837050 61.6903290 34.7647482 9.8616087 32 33 34 35 36 37 140.0926190 -281.2432783 143.0115379 60.6737638 -118.9049566 293.5667231 38 39 40 41 42 43 6.9601361 82.7355952 -78.7855450 271.8625074 61.7312052 133.7354709 44 45 46 47 48 49 -176.4111208 13.8828869 53.3356333 243.7134204 266.7701229 76.3604471 50 51 52 53 54 55 203.5162868 -168.0132248 387.4861668 112.3385200 17.9893239 212.4904044 56 57 58 59 60 61 32.2509338 212.2995771 5.7786575 -79.8233078 -78.8519773 -135.0559317 62 63 64 65 66 67 13.1528600 -42.7409446 -92.6064143 147.0613176 157.6586013 -1.9997423 68 69 70 71 72 73 141.2578861 156.1074626 55.7257192 -93.6710929 -153.5142887 -103.0426090 74 75 76 77 78 79 -106.8604354 149.7029320 -137.1431425 -54.3758772 -96.4603137 -128.7011282 80 81 82 83 84 85 -13.6356281 0.9225708 -265.3399597 3.2701668 104.1217162 -274.8906782 86 87 88 89 90 91 257.8019034 -243.1454214 16.2214483 -39.7005136 -203.7253437 25.1996362 92 93 94 95 96 97 -263.5762921 96.9228686 -52.4128614 -32.2402275 161.6049515 -129.0631134 98 99 100 101 102 103 -78.3508525 -94.0126018 32.6650408 -169.3761340 89.8906976 -74.0260351 104 105 106 107 108 109 61.9269067 -171.9321393 -45.5120971 53.7001797 90.9160221 220.7580810 110 111 112 113 114 115 -169.9674347 36.2322079 18.6977587 -136.4823083 174.9037362 11.4968431 116 117 118 119 120 121 -0.8549016 -30.7203180 -104.7641022 115.3225914 121.9886671 63.4201356 122 123 124 125 126 127 -100.6427710 254.8016677 -74.1702741 -16.9791094 -63.8118112 -106.7479392 128 129 130 131 132 133 47.5626411 26.3459566 -125.2609034 107.7794929 95.5647813 -44.8778828 134 135 136 137 138 139 -95.6690912 53.8679423 -28.9778480 -55.9061803 92.3207243 -111.3972257 140 141 142 143 144 145 38.6419405 -59.0316317 110.6928129 -252.8434598 -12.0573188 -84.3874247 146 147 148 149 150 151 113.0861265 49.0398365 6.5120418 0.3452839 -70.6728917 152.7486188 152 153 154 155 156 157 -88.6896345 106.7829082 161.7917917 -170.0888104 -285.8987336 22.0830699 158 159 160 161 162 163 120.1853895 -19.5099165 23.6379228 -3.4295858 131.4330258 -81.3445306 164 165 166 167 168 169 176.9330613 -61.8400444 130.4474760 17.0966770 8.7896549 -116.3746566 170 171 172 173 174 175 -172.1699053 63.8309545 68.5083130 -34.2811271 -101.8091424 -24.2021582 176 177 178 179 180 181 -85.9315049 175.6799300 -28.2981616 -189.8075321 -168.5844669 162.2711852 182 183 184 185 186 187 18.9759392 81.1750135 -12.8362870 68.0102641 -14.5643327 -23.3879024 188 189 190 191 192 44.2007465 126.4212704 61.2579892 28.1325910 -42.5916760 > postscript(file="/var/wessaorg/rcomp/tmp/6sxxq1383550854.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 191 Frequency = 1 lag(myerror, k = 1) myerror 0 -76.5156196 NA 1 -139.2039870 -76.5156196 2 -120.6985092 -139.2039870 3 -6.3421184 -120.6985092 4 -129.7049076 -6.3421184 5 -122.7602484 -129.7049076 6 -51.9994348 -122.7602484 7 -185.5471398 -51.9994348 8 -195.9219444 -185.5471398 9 138.1514402 -195.9219444 10 -141.1165074 138.1514402 11 -32.2475463 -141.1165074 12 156.6099772 -32.2475463 13 -54.8006057 156.6099772 14 -48.3943772 -54.8006057 15 -144.4352678 -48.3943772 16 -79.9433196 -144.4352678 17 129.0343280 -79.9433196 18 -1.7682183 129.0343280 19 -125.0508796 -1.7682183 20 95.4684120 -125.0508796 21 50.6341072 95.4684120 22 151.7640093 50.6341072 23 81.4802009 151.7640093 24 -90.1125089 81.4802009 25 -9.9594478 -90.1125089 26 39.8837050 -9.9594478 27 61.6903290 39.8837050 28 34.7647482 61.6903290 29 9.8616087 34.7647482 30 140.0926190 9.8616087 31 -281.2432783 140.0926190 32 143.0115379 -281.2432783 33 60.6737638 143.0115379 34 -118.9049566 60.6737638 35 293.5667231 -118.9049566 36 6.9601361 293.5667231 37 82.7355952 6.9601361 38 -78.7855450 82.7355952 39 271.8625074 -78.7855450 40 61.7312052 271.8625074 41 133.7354709 61.7312052 42 -176.4111208 133.7354709 43 13.8828869 -176.4111208 44 53.3356333 13.8828869 45 243.7134204 53.3356333 46 266.7701229 243.7134204 47 76.3604471 266.7701229 48 203.5162868 76.3604471 49 -168.0132248 203.5162868 50 387.4861668 -168.0132248 51 112.3385200 387.4861668 52 17.9893239 112.3385200 53 212.4904044 17.9893239 54 32.2509338 212.4904044 55 212.2995771 32.2509338 56 5.7786575 212.2995771 57 -79.8233078 5.7786575 58 -78.8519773 -79.8233078 59 -135.0559317 -78.8519773 60 13.1528600 -135.0559317 61 -42.7409446 13.1528600 62 -92.6064143 -42.7409446 63 147.0613176 -92.6064143 64 157.6586013 147.0613176 65 -1.9997423 157.6586013 66 141.2578861 -1.9997423 67 156.1074626 141.2578861 68 55.7257192 156.1074626 69 -93.6710929 55.7257192 70 -153.5142887 -93.6710929 71 -103.0426090 -153.5142887 72 -106.8604354 -103.0426090 73 149.7029320 -106.8604354 74 -137.1431425 149.7029320 75 -54.3758772 -137.1431425 76 -96.4603137 -54.3758772 77 -128.7011282 -96.4603137 78 -13.6356281 -128.7011282 79 0.9225708 -13.6356281 80 -265.3399597 0.9225708 81 3.2701668 -265.3399597 82 104.1217162 3.2701668 83 -274.8906782 104.1217162 84 257.8019034 -274.8906782 85 -243.1454214 257.8019034 86 16.2214483 -243.1454214 87 -39.7005136 16.2214483 88 -203.7253437 -39.7005136 89 25.1996362 -203.7253437 90 -263.5762921 25.1996362 91 96.9228686 -263.5762921 92 -52.4128614 96.9228686 93 -32.2402275 -52.4128614 94 161.6049515 -32.2402275 95 -129.0631134 161.6049515 96 -78.3508525 -129.0631134 97 -94.0126018 -78.3508525 98 32.6650408 -94.0126018 99 -169.3761340 32.6650408 100 89.8906976 -169.3761340 101 -74.0260351 89.8906976 102 61.9269067 -74.0260351 103 -171.9321393 61.9269067 104 -45.5120971 -171.9321393 105 53.7001797 -45.5120971 106 90.9160221 53.7001797 107 220.7580810 90.9160221 108 -169.9674347 220.7580810 109 36.2322079 -169.9674347 110 18.6977587 36.2322079 111 -136.4823083 18.6977587 112 174.9037362 -136.4823083 113 11.4968431 174.9037362 114 -0.8549016 11.4968431 115 -30.7203180 -0.8549016 116 -104.7641022 -30.7203180 117 115.3225914 -104.7641022 118 121.9886671 115.3225914 119 63.4201356 121.9886671 120 -100.6427710 63.4201356 121 254.8016677 -100.6427710 122 -74.1702741 254.8016677 123 -16.9791094 -74.1702741 124 -63.8118112 -16.9791094 125 -106.7479392 -63.8118112 126 47.5626411 -106.7479392 127 26.3459566 47.5626411 128 -125.2609034 26.3459566 129 107.7794929 -125.2609034 130 95.5647813 107.7794929 131 -44.8778828 95.5647813 132 -95.6690912 -44.8778828 133 53.8679423 -95.6690912 134 -28.9778480 53.8679423 135 -55.9061803 -28.9778480 136 92.3207243 -55.9061803 137 -111.3972257 92.3207243 138 38.6419405 -111.3972257 139 -59.0316317 38.6419405 140 110.6928129 -59.0316317 141 -252.8434598 110.6928129 142 -12.0573188 -252.8434598 143 -84.3874247 -12.0573188 144 113.0861265 -84.3874247 145 49.0398365 113.0861265 146 6.5120418 49.0398365 147 0.3452839 6.5120418 148 -70.6728917 0.3452839 149 152.7486188 -70.6728917 150 -88.6896345 152.7486188 151 106.7829082 -88.6896345 152 161.7917917 106.7829082 153 -170.0888104 161.7917917 154 -285.8987336 -170.0888104 155 22.0830699 -285.8987336 156 120.1853895 22.0830699 157 -19.5099165 120.1853895 158 23.6379228 -19.5099165 159 -3.4295858 23.6379228 160 131.4330258 -3.4295858 161 -81.3445306 131.4330258 162 176.9330613 -81.3445306 163 -61.8400444 176.9330613 164 130.4474760 -61.8400444 165 17.0966770 130.4474760 166 8.7896549 17.0966770 167 -116.3746566 8.7896549 168 -172.1699053 -116.3746566 169 63.8309545 -172.1699053 170 68.5083130 63.8309545 171 -34.2811271 68.5083130 172 -101.8091424 -34.2811271 173 -24.2021582 -101.8091424 174 -85.9315049 -24.2021582 175 175.6799300 -85.9315049 176 -28.2981616 175.6799300 177 -189.8075321 -28.2981616 178 -168.5844669 -189.8075321 179 162.2711852 -168.5844669 180 18.9759392 162.2711852 181 81.1750135 18.9759392 182 -12.8362870 81.1750135 183 68.0102641 -12.8362870 184 -14.5643327 68.0102641 185 -23.3879024 -14.5643327 186 44.2007465 -23.3879024 187 126.4212704 44.2007465 188 61.2579892 126.4212704 189 28.1325910 61.2579892 190 -42.5916760 28.1325910 191 NA -42.5916760 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -139.2039870 -76.5156196 [2,] -120.6985092 -139.2039870 [3,] -6.3421184 -120.6985092 [4,] -129.7049076 -6.3421184 [5,] -122.7602484 -129.7049076 [6,] -51.9994348 -122.7602484 [7,] -185.5471398 -51.9994348 [8,] -195.9219444 -185.5471398 [9,] 138.1514402 -195.9219444 [10,] -141.1165074 138.1514402 [11,] -32.2475463 -141.1165074 [12,] 156.6099772 -32.2475463 [13,] -54.8006057 156.6099772 [14,] -48.3943772 -54.8006057 [15,] -144.4352678 -48.3943772 [16,] -79.9433196 -144.4352678 [17,] 129.0343280 -79.9433196 [18,] -1.7682183 129.0343280 [19,] -125.0508796 -1.7682183 [20,] 95.4684120 -125.0508796 [21,] 50.6341072 95.4684120 [22,] 151.7640093 50.6341072 [23,] 81.4802009 151.7640093 [24,] -90.1125089 81.4802009 [25,] -9.9594478 -90.1125089 [26,] 39.8837050 -9.9594478 [27,] 61.6903290 39.8837050 [28,] 34.7647482 61.6903290 [29,] 9.8616087 34.7647482 [30,] 140.0926190 9.8616087 [31,] -281.2432783 140.0926190 [32,] 143.0115379 -281.2432783 [33,] 60.6737638 143.0115379 [34,] -118.9049566 60.6737638 [35,] 293.5667231 -118.9049566 [36,] 6.9601361 293.5667231 [37,] 82.7355952 6.9601361 [38,] -78.7855450 82.7355952 [39,] 271.8625074 -78.7855450 [40,] 61.7312052 271.8625074 [41,] 133.7354709 61.7312052 [42,] -176.4111208 133.7354709 [43,] 13.8828869 -176.4111208 [44,] 53.3356333 13.8828869 [45,] 243.7134204 53.3356333 [46,] 266.7701229 243.7134204 [47,] 76.3604471 266.7701229 [48,] 203.5162868 76.3604471 [49,] -168.0132248 203.5162868 [50,] 387.4861668 -168.0132248 [51,] 112.3385200 387.4861668 [52,] 17.9893239 112.3385200 [53,] 212.4904044 17.9893239 [54,] 32.2509338 212.4904044 [55,] 212.2995771 32.2509338 [56,] 5.7786575 212.2995771 [57,] -79.8233078 5.7786575 [58,] -78.8519773 -79.8233078 [59,] -135.0559317 -78.8519773 [60,] 13.1528600 -135.0559317 [61,] -42.7409446 13.1528600 [62,] -92.6064143 -42.7409446 [63,] 147.0613176 -92.6064143 [64,] 157.6586013 147.0613176 [65,] -1.9997423 157.6586013 [66,] 141.2578861 -1.9997423 [67,] 156.1074626 141.2578861 [68,] 55.7257192 156.1074626 [69,] -93.6710929 55.7257192 [70,] -153.5142887 -93.6710929 [71,] -103.0426090 -153.5142887 [72,] -106.8604354 -103.0426090 [73,] 149.7029320 -106.8604354 [74,] -137.1431425 149.7029320 [75,] -54.3758772 -137.1431425 [76,] -96.4603137 -54.3758772 [77,] -128.7011282 -96.4603137 [78,] -13.6356281 -128.7011282 [79,] 0.9225708 -13.6356281 [80,] -265.3399597 0.9225708 [81,] 3.2701668 -265.3399597 [82,] 104.1217162 3.2701668 [83,] -274.8906782 104.1217162 [84,] 257.8019034 -274.8906782 [85,] -243.1454214 257.8019034 [86,] 16.2214483 -243.1454214 [87,] -39.7005136 16.2214483 [88,] -203.7253437 -39.7005136 [89,] 25.1996362 -203.7253437 [90,] -263.5762921 25.1996362 [91,] 96.9228686 -263.5762921 [92,] -52.4128614 96.9228686 [93,] -32.2402275 -52.4128614 [94,] 161.6049515 -32.2402275 [95,] -129.0631134 161.6049515 [96,] -78.3508525 -129.0631134 [97,] -94.0126018 -78.3508525 [98,] 32.6650408 -94.0126018 [99,] -169.3761340 32.6650408 [100,] 89.8906976 -169.3761340 [101,] -74.0260351 89.8906976 [102,] 61.9269067 -74.0260351 [103,] -171.9321393 61.9269067 [104,] -45.5120971 -171.9321393 [105,] 53.7001797 -45.5120971 [106,] 90.9160221 53.7001797 [107,] 220.7580810 90.9160221 [108,] -169.9674347 220.7580810 [109,] 36.2322079 -169.9674347 [110,] 18.6977587 36.2322079 [111,] -136.4823083 18.6977587 [112,] 174.9037362 -136.4823083 [113,] 11.4968431 174.9037362 [114,] -0.8549016 11.4968431 [115,] -30.7203180 -0.8549016 [116,] -104.7641022 -30.7203180 [117,] 115.3225914 -104.7641022 [118,] 121.9886671 115.3225914 [119,] 63.4201356 121.9886671 [120,] -100.6427710 63.4201356 [121,] 254.8016677 -100.6427710 [122,] -74.1702741 254.8016677 [123,] -16.9791094 -74.1702741 [124,] -63.8118112 -16.9791094 [125,] -106.7479392 -63.8118112 [126,] 47.5626411 -106.7479392 [127,] 26.3459566 47.5626411 [128,] -125.2609034 26.3459566 [129,] 107.7794929 -125.2609034 [130,] 95.5647813 107.7794929 [131,] -44.8778828 95.5647813 [132,] -95.6690912 -44.8778828 [133,] 53.8679423 -95.6690912 [134,] -28.9778480 53.8679423 [135,] -55.9061803 -28.9778480 [136,] 92.3207243 -55.9061803 [137,] -111.3972257 92.3207243 [138,] 38.6419405 -111.3972257 [139,] -59.0316317 38.6419405 [140,] 110.6928129 -59.0316317 [141,] -252.8434598 110.6928129 [142,] -12.0573188 -252.8434598 [143,] -84.3874247 -12.0573188 [144,] 113.0861265 -84.3874247 [145,] 49.0398365 113.0861265 [146,] 6.5120418 49.0398365 [147,] 0.3452839 6.5120418 [148,] -70.6728917 0.3452839 [149,] 152.7486188 -70.6728917 [150,] -88.6896345 152.7486188 [151,] 106.7829082 -88.6896345 [152,] 161.7917917 106.7829082 [153,] -170.0888104 161.7917917 [154,] -285.8987336 -170.0888104 [155,] 22.0830699 -285.8987336 [156,] 120.1853895 22.0830699 [157,] -19.5099165 120.1853895 [158,] 23.6379228 -19.5099165 [159,] -3.4295858 23.6379228 [160,] 131.4330258 -3.4295858 [161,] -81.3445306 131.4330258 [162,] 176.9330613 -81.3445306 [163,] -61.8400444 176.9330613 [164,] 130.4474760 -61.8400444 [165,] 17.0966770 130.4474760 [166,] 8.7896549 17.0966770 [167,] -116.3746566 8.7896549 [168,] -172.1699053 -116.3746566 [169,] 63.8309545 -172.1699053 [170,] 68.5083130 63.8309545 [171,] -34.2811271 68.5083130 [172,] -101.8091424 -34.2811271 [173,] -24.2021582 -101.8091424 [174,] -85.9315049 -24.2021582 [175,] 175.6799300 -85.9315049 [176,] -28.2981616 175.6799300 [177,] -189.8075321 -28.2981616 [178,] -168.5844669 -189.8075321 [179,] 162.2711852 -168.5844669 [180,] 18.9759392 162.2711852 [181,] 81.1750135 18.9759392 [182,] -12.8362870 81.1750135 [183,] 68.0102641 -12.8362870 [184,] -14.5643327 68.0102641 [185,] -23.3879024 -14.5643327 [186,] 44.2007465 -23.3879024 [187,] 126.4212704 44.2007465 [188,] 61.2579892 126.4212704 [189,] 28.1325910 61.2579892 [190,] -42.5916760 28.1325910 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -139.2039870 -76.5156196 2 -120.6985092 -139.2039870 3 -6.3421184 -120.6985092 4 -129.7049076 -6.3421184 5 -122.7602484 -129.7049076 6 -51.9994348 -122.7602484 7 -185.5471398 -51.9994348 8 -195.9219444 -185.5471398 9 138.1514402 -195.9219444 10 -141.1165074 138.1514402 11 -32.2475463 -141.1165074 12 156.6099772 -32.2475463 13 -54.8006057 156.6099772 14 -48.3943772 -54.8006057 15 -144.4352678 -48.3943772 16 -79.9433196 -144.4352678 17 129.0343280 -79.9433196 18 -1.7682183 129.0343280 19 -125.0508796 -1.7682183 20 95.4684120 -125.0508796 21 50.6341072 95.4684120 22 151.7640093 50.6341072 23 81.4802009 151.7640093 24 -90.1125089 81.4802009 25 -9.9594478 -90.1125089 26 39.8837050 -9.9594478 27 61.6903290 39.8837050 28 34.7647482 61.6903290 29 9.8616087 34.7647482 30 140.0926190 9.8616087 31 -281.2432783 140.0926190 32 143.0115379 -281.2432783 33 60.6737638 143.0115379 34 -118.9049566 60.6737638 35 293.5667231 -118.9049566 36 6.9601361 293.5667231 37 82.7355952 6.9601361 38 -78.7855450 82.7355952 39 271.8625074 -78.7855450 40 61.7312052 271.8625074 41 133.7354709 61.7312052 42 -176.4111208 133.7354709 43 13.8828869 -176.4111208 44 53.3356333 13.8828869 45 243.7134204 53.3356333 46 266.7701229 243.7134204 47 76.3604471 266.7701229 48 203.5162868 76.3604471 49 -168.0132248 203.5162868 50 387.4861668 -168.0132248 51 112.3385200 387.4861668 52 17.9893239 112.3385200 53 212.4904044 17.9893239 54 32.2509338 212.4904044 55 212.2995771 32.2509338 56 5.7786575 212.2995771 57 -79.8233078 5.7786575 58 -78.8519773 -79.8233078 59 -135.0559317 -78.8519773 60 13.1528600 -135.0559317 61 -42.7409446 13.1528600 62 -92.6064143 -42.7409446 63 147.0613176 -92.6064143 64 157.6586013 147.0613176 65 -1.9997423 157.6586013 66 141.2578861 -1.9997423 67 156.1074626 141.2578861 68 55.7257192 156.1074626 69 -93.6710929 55.7257192 70 -153.5142887 -93.6710929 71 -103.0426090 -153.5142887 72 -106.8604354 -103.0426090 73 149.7029320 -106.8604354 74 -137.1431425 149.7029320 75 -54.3758772 -137.1431425 76 -96.4603137 -54.3758772 77 -128.7011282 -96.4603137 78 -13.6356281 -128.7011282 79 0.9225708 -13.6356281 80 -265.3399597 0.9225708 81 3.2701668 -265.3399597 82 104.1217162 3.2701668 83 -274.8906782 104.1217162 84 257.8019034 -274.8906782 85 -243.1454214 257.8019034 86 16.2214483 -243.1454214 87 -39.7005136 16.2214483 88 -203.7253437 -39.7005136 89 25.1996362 -203.7253437 90 -263.5762921 25.1996362 91 96.9228686 -263.5762921 92 -52.4128614 96.9228686 93 -32.2402275 -52.4128614 94 161.6049515 -32.2402275 95 -129.0631134 161.6049515 96 -78.3508525 -129.0631134 97 -94.0126018 -78.3508525 98 32.6650408 -94.0126018 99 -169.3761340 32.6650408 100 89.8906976 -169.3761340 101 -74.0260351 89.8906976 102 61.9269067 -74.0260351 103 -171.9321393 61.9269067 104 -45.5120971 -171.9321393 105 53.7001797 -45.5120971 106 90.9160221 53.7001797 107 220.7580810 90.9160221 108 -169.9674347 220.7580810 109 36.2322079 -169.9674347 110 18.6977587 36.2322079 111 -136.4823083 18.6977587 112 174.9037362 -136.4823083 113 11.4968431 174.9037362 114 -0.8549016 11.4968431 115 -30.7203180 -0.8549016 116 -104.7641022 -30.7203180 117 115.3225914 -104.7641022 118 121.9886671 115.3225914 119 63.4201356 121.9886671 120 -100.6427710 63.4201356 121 254.8016677 -100.6427710 122 -74.1702741 254.8016677 123 -16.9791094 -74.1702741 124 -63.8118112 -16.9791094 125 -106.7479392 -63.8118112 126 47.5626411 -106.7479392 127 26.3459566 47.5626411 128 -125.2609034 26.3459566 129 107.7794929 -125.2609034 130 95.5647813 107.7794929 131 -44.8778828 95.5647813 132 -95.6690912 -44.8778828 133 53.8679423 -95.6690912 134 -28.9778480 53.8679423 135 -55.9061803 -28.9778480 136 92.3207243 -55.9061803 137 -111.3972257 92.3207243 138 38.6419405 -111.3972257 139 -59.0316317 38.6419405 140 110.6928129 -59.0316317 141 -252.8434598 110.6928129 142 -12.0573188 -252.8434598 143 -84.3874247 -12.0573188 144 113.0861265 -84.3874247 145 49.0398365 113.0861265 146 6.5120418 49.0398365 147 0.3452839 6.5120418 148 -70.6728917 0.3452839 149 152.7486188 -70.6728917 150 -88.6896345 152.7486188 151 106.7829082 -88.6896345 152 161.7917917 106.7829082 153 -170.0888104 161.7917917 154 -285.8987336 -170.0888104 155 22.0830699 -285.8987336 156 120.1853895 22.0830699 157 -19.5099165 120.1853895 158 23.6379228 -19.5099165 159 -3.4295858 23.6379228 160 131.4330258 -3.4295858 161 -81.3445306 131.4330258 162 176.9330613 -81.3445306 163 -61.8400444 176.9330613 164 130.4474760 -61.8400444 165 17.0966770 130.4474760 166 8.7896549 17.0966770 167 -116.3746566 8.7896549 168 -172.1699053 -116.3746566 169 63.8309545 -172.1699053 170 68.5083130 63.8309545 171 -34.2811271 68.5083130 172 -101.8091424 -34.2811271 173 -24.2021582 -101.8091424 174 -85.9315049 -24.2021582 175 175.6799300 -85.9315049 176 -28.2981616 175.6799300 177 -189.8075321 -28.2981616 178 -168.5844669 -189.8075321 179 162.2711852 -168.5844669 180 18.9759392 162.2711852 181 81.1750135 18.9759392 182 -12.8362870 81.1750135 183 68.0102641 -12.8362870 184 -14.5643327 68.0102641 185 -23.3879024 -14.5643327 186 44.2007465 -23.3879024 187 126.4212704 44.2007465 188 61.2579892 126.4212704 189 28.1325910 61.2579892 190 -42.5916760 28.1325910 > 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/wessaorg/rcomp/tmp/7p0pj1383550854.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/8bvz61383550854.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/9jgrf1383550854.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/10wbaf1383550854.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11ky6a1383550854.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,signif(mysum$coefficients[i,1],6)) + a<-table.element(a, signif(mysum$coefficients[i,2],6)) + a<-table.element(a, signif(mysum$coefficients[i,3],4)) + a<-table.element(a, signif(mysum$coefficients[i,4],6)) + a<-table.element(a, signif(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12rgy91383550854.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, signif(sqrt(mysum$r.squared),6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, signif(mysum$r.squared,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, signif(mysum$adj.r.squared,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[1],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[2],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[3],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6)) > 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, signif(mysum$sigma,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, signif(sum(myerror*myerror),6)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13j63s1383550854.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,signif(x[i],6)) + a<-table.element(a,signif(x[i]-mysum$resid[i],6)) + a<-table.element(a,signif(mysum$resid[i],6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14efwa1383550854.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,signif(gqarr[mypoint-kp3+1,1],6)) + a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6)) + a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6)) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/153yet1383550854.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,signif(numsignificant1,6)) + a<-table.element(a,signif(numsignificant1/numgqtests,6)) + 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,signif(numsignificant5,6)) + a<-table.element(a,signif(numsignificant5/numgqtests,6)) + 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,signif(numsignificant10,6)) + a<-table.element(a,signif(numsignificant10/numgqtests,6)) + 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/wessaorg/rcomp/tmp/16g3h61383550854.tab") + } > > try(system("convert tmp/1rypm1383550854.ps tmp/1rypm1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/2hf0c1383550854.ps tmp/2hf0c1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/3bph21383550854.ps tmp/3bph21383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/4axfo1383550854.ps tmp/4axfo1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/5bmts1383550854.ps tmp/5bmts1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/6sxxq1383550854.ps tmp/6sxxq1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/7p0pj1383550854.ps tmp/7p0pj1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/8bvz61383550854.ps tmp/8bvz61383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/9jgrf1383550854.ps tmp/9jgrf1383550854.png",intern=TRUE)) character(0) > try(system("convert tmp/10wbaf1383550854.ps tmp/10wbaf1383550854.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 14.145 2.374 16.527