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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 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal 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 1 1687 0 NA 2 1508 0 1687 3 1507 0 1508 4 1385 0 1507 5 1632 0 1385 6 1511 0 1632 7 1559 0 1511 8 1630 0 1559 9 1579 0 1630 10 1653 0 1579 11 2152 0 1653 12 2148 0 2152 13 1752 0 2148 14 1765 0 1752 15 1717 0 1765 16 1558 0 1717 17 1575 0 1558 18 1520 0 1575 19 1805 0 1520 20 1800 0 1805 21 1719 0 1800 22 2008 0 1719 23 2242 0 2008 24 2478 0 2242 25 2030 0 2478 26 1655 0 2030 27 1693 0 1655 28 1623 0 1693 29 1805 0 1623 30 1746 0 1805 31 1795 0 1746 32 1926 0 1795 33 1619 0 1926 34 1992 0 1619 35 2233 0 1992 36 2192 0 2233 37 2080 0 2192 38 1768 0 2080 39 1835 0 1768 40 1569 0 1835 41 1976 0 1569 42 1853 0 1976 43 1965 0 1853 44 1689 0 1965 45 1778 0 1689 46 1976 0 1778 47 2397 0 1976 48 2654 0 2397 49 2097 0 2654 50 1963 0 2097 51 1677 0 1963 52 1941 0 1677 53 2003 0 1941 54 1813 0 2003 55 2012 0 1813 56 1912 0 2012 57 2084 0 1912 58 2080 0 2084 59 2118 0 2080 60 2150 0 2118 61 1608 0 2150 62 1503 0 1608 63 1548 0 1503 64 1382 0 1548 65 1731 0 1382 66 1798 0 1731 67 1779 0 1798 68 1887 0 1779 69 2004 0 1887 70 2077 0 2004 71 2092 0 2077 72 2051 0 2092 73 1577 0 2051 74 1356 0 1577 75 1652 0 1356 76 1382 0 1652 77 1519 0 1382 78 1421 0 1519 79 1442 0 1421 80 1543 0 1442 81 1656 0 1543 82 1561 0 1656 83 1905 0 1561 84 2199 0 1905 85 1473 0 2199 86 1655 0 1473 87 1407 0 1655 88 1395 0 1407 89 1530 0 1395 90 1309 0 1530 91 1526 0 1309 92 1327 0 1526 93 1627 0 1327 94 1748 0 1627 95 1958 0 1748 96 2274 0 1958 97 1648 0 2274 98 1401 0 1648 99 1411 0 1401 100 1403 0 1411 101 1394 0 1403 102 1520 0 1394 103 1528 0 1520 104 1643 0 1528 105 1515 0 1643 106 1685 0 1515 107 2000 0 1685 108 2215 0 2000 109 1956 0 2215 110 1462 0 1956 111 1563 0 1462 112 1459 0 1563 113 1446 0 1459 114 1622 0 1446 115 1657 0 1622 116 1638 0 1657 117 1643 0 1638 118 1683 0 1643 119 2050 0 1683 120 2262 0 2050 121 1813 0 2262 122 1445 0 1813 123 1762 0 1445 124 1461 0 1762 125 1556 0 1461 126 1431 0 1556 127 1427 0 1431 128 1554 0 1427 129 1645 0 1554 130 1653 0 1645 131 2016 0 1653 132 2207 0 2016 133 1665 0 2207 134 1361 0 1665 135 1506 0 1361 136 1360 0 1506 137 1453 0 1360 138 1522 0 1453 139 1460 0 1522 140 1552 0 1460 141 1548 0 1552 142 1827 0 1548 143 1737 0 1827 144 1941 0 1737 145 1474 0 1941 146 1458 0 1474 147 1542 0 1458 148 1404 0 1542 149 1522 0 1404 150 1385 0 1522 151 1641 0 1385 152 1510 0 1641 153 1681 0 1510 154 1938 0 1681 155 1868 0 1938 156 1726 0 1868 157 1456 0 1726 158 1445 0 1456 159 1456 0 1445 160 1365 0 1456 161 1487 0 1365 162 1558 0 1487 163 1488 0 1558 164 1684 0 1488 165 1594 0 1684 166 1850 0 1594 167 1998 0 1850 168 2079 0 1998 169 1494 0 2079 170 1057 1 1494 171 1218 1 1057 172 1168 1 1218 173 1236 1 1168 174 1076 1 1236 175 1174 1 1076 176 1139 1 1174 177 1427 1 1139 178 1487 1 1427 179 1483 1 1487 180 1513 1 1483 181 1357 1 1513 182 1165 1 1357 183 1282 1 1165 184 1110 1 1282 185 1297 1 1110 186 1185 1 1297 187 1222 1 1185 188 1284 1 1222 189 1444 1 1284 190 1575 1 1444 191 1737 1 1575 192 1763 1 1737 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Belt A1 617.4672 -134.3651 0.6401 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -552.15 -130.07 3.14 143.98 514.60 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 617.46722 98.95216 6.240 2.83e-09 *** Belt -134.36510 50.56941 -2.657 0.00856 ** A1 0.64015 0.05684 11.262 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 202 on 188 degrees of freedom (1 observation deleted due to missingness) Multiple R-squared: 0.5212, Adjusted R-squared: 0.5162 F-statistic: 102.3 on 2 and 188 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,] 0.12114543 0.24229086 0.878854570 [2,] 0.08465125 0.16930250 0.915348750 [3,] 0.04135086 0.08270172 0.958649141 [4,] 0.03057196 0.06114392 0.969428040 [5,] 0.71210845 0.57578309 0.287891547 [6,] 0.62882121 0.74235758 0.371178788 [7,] 0.68121676 0.63756648 0.318783241 [8,] 0.59540571 0.80918859 0.404594294 [9,] 0.50473210 0.99053580 0.495267900 [10,] 0.45837047 0.91674094 0.541629529 [11,] 0.37556207 0.75112415 0.624437927 [12,] 0.31322556 0.62645112 0.686774438 [13,] 0.33648840 0.67297681 0.663511597 [14,] 0.27226157 0.54452314 0.727738429 [15,] 0.21330239 0.42660479 0.786697607 [16,] 0.29687512 0.59375024 0.703124878 [17,] 0.41540299 0.83080598 0.584597012 [18,] 0.52696084 0.94607832 0.473039161 [19,] 0.60107411 0.79785177 0.398925885 [20,] 0.65861776 0.68276448 0.341382240 [21,] 0.59849219 0.80301563 0.401507815 [22,] 0.54777230 0.90445539 0.452227696 [23,] 0.51496942 0.97006116 0.485030582 [24,] 0.45636093 0.91272187 0.543639066 [25,] 0.40037351 0.80074703 0.599626486 [26,] 0.37268751 0.74537503 0.627312486 [27,] 0.40045805 0.80091611 0.599541947 [28,] 0.48780588 0.97561176 0.512194121 [29,] 0.56983008 0.86033983 0.430169916 [30,] 0.53148897 0.93702207 0.468511034 [31,] 0.47792607 0.95585215 0.522073926 [32,] 0.48256393 0.96512787 0.517436066 [33,] 0.43441826 0.86883652 0.565581742 [34,] 0.45852087 0.91704174 0.541479130 [35,] 0.54489003 0.91021995 0.455109973 [36,] 0.49622463 0.99244926 0.503775368 [37,] 0.46920425 0.93840849 0.530795754 [38,] 0.47024454 0.94048908 0.529755461 [39,] 0.42404972 0.84809945 0.575950277 [40,] 0.42204271 0.84408542 0.577957289 [41,] 0.65771193 0.68457614 0.342288072 [42,] 0.81703712 0.36592576 0.182962879 [43,] 0.83911857 0.32176286 0.160881430 [44,] 0.80978967 0.38042067 0.190210334 [45,] 0.81479287 0.37041427 0.185207135 [46,] 0.82052190 0.35895620 0.179478099 [47,] 0.80066926 0.39866148 0.199330740 [48,] 0.77719184 0.44561632 0.222808162 [49,] 0.77967593 0.44064815 0.220324075 [50,] 0.74559358 0.50881284 0.254406422 [51,] 0.75345097 0.49309806 0.246549029 [52,] 0.73001065 0.53997871 0.269989353 [53,] 0.71648047 0.56703907 0.283519535 [54,] 0.70668705 0.58662590 0.293312951 [55,] 0.80631401 0.38737197 0.193685987 [56,] 0.79808902 0.40382195 0.201910976 [57,] 0.76904458 0.46191084 0.230955422 [58,] 0.78573691 0.42852618 0.214263092 [59,] 0.78591660 0.42816681 0.214083404 [60,] 0.75637601 0.48724799 0.243623994 [61,] 0.72225623 0.55548755 0.277743774 [62,] 0.69888643 0.60222714 0.301113568 [63,] 0.68966052 0.62067896 0.310339481 [64,] 0.68274790 0.63450419 0.317252097 [65,] 0.66885079 0.66229842 0.331149212 [66,] 0.64413066 0.71173868 0.355869339 [67,] 0.72471091 0.55057818 0.275289091 [68,] 0.76124935 0.47750129 0.238750647 [69,] 0.74455786 0.51088429 0.255442143 [70,] 0.78632760 0.42734480 0.213672402 [71,] 0.75441237 0.49117527 0.245587633 [72,] 0.74806894 0.50386212 0.251931059 [73,] 0.72168024 0.55663952 0.278319759 [74,] 0.68536808 0.62926385 0.314631924 [75,] 0.64931749 0.70136502 0.350682512 [76,] 0.62431979 0.75136042 0.375680209 [77,] 0.66324277 0.67351446 0.336757229 [78,] 0.75322496 0.49355009 0.246775044 [79,] 0.90410193 0.19179613 0.095898066 [80,] 0.88911974 0.22176053 0.110880263 [81,] 0.90414381 0.19171239 0.095856194 [82,] 0.89368853 0.21262294 0.106311472 [83,] 0.87351154 0.25297691 0.126488456 [84,] 0.89496931 0.21006139 0.105030694 [85,] 0.87676248 0.24647505 0.123237523 [86,] 0.89207774 0.21584452 0.107922261 [87,] 0.88370983 0.23258034 0.116290169 [88,] 0.86722023 0.26555954 0.132779770 [89,] 0.87487435 0.25025130 0.125125649 [90,] 0.93660431 0.12679138 0.063395691 [91,] 0.96532428 0.06935144 0.034675721 [92,] 0.97084960 0.05830080 0.029150401 [93,] 0.96544370 0.06911260 0.034556299 [94,] 0.95991864 0.08016273 0.040081363 [95,] 0.95393465 0.09213071 0.046065353 [96,] 0.94289759 0.11420482 0.057102409 [97,] 0.93105523 0.13788954 0.068944770 [98,] 0.91716537 0.16566926 0.082834631 [99,] 0.90926343 0.18147314 0.090736569 [100,] 0.89598039 0.20803922 0.104019610 [101,] 0.92251042 0.15497916 0.077489582 [102,] 0.95118079 0.09763842 0.048819211 [103,] 0.94088601 0.11822797 0.059113987 [104,] 0.96675220 0.06649560 0.033247799 [105,] 0.95813845 0.08372310 0.041861550 [106,] 0.95377494 0.09245013 0.046225064 [107,] 0.94553673 0.10892655 0.054463274 [108,] 0.93511801 0.12976398 0.064881989 [109,] 0.92059529 0.15880942 0.079404711 [110,] 0.90384569 0.19230861 0.096154307 [111,] 0.88431569 0.23136861 0.115684306 [112,] 0.86263816 0.27472368 0.137361839 [113,] 0.91615556 0.16768888 0.083844438 [114,] 0.95668099 0.08663803 0.043319015 [115,] 0.95523450 0.08953101 0.044765504 [116,] 0.96719985 0.06560030 0.032800151 [117,] 0.97068807 0.05862385 0.029311925 [118,] 0.97550679 0.04898641 0.024493206 [119,] 0.96844602 0.06310796 0.031553982 [120,] 0.96603398 0.06793204 0.033966022 [121,] 0.95903646 0.08192708 0.040963539 [122,] 0.94844770 0.10310459 0.051552296 [123,] 0.93638085 0.12723830 0.063619149 [124,] 0.92105282 0.15789436 0.078947181 [125,] 0.95692760 0.08614480 0.043072400 [126,] 0.97920780 0.04158439 0.020792196 [127,] 0.98536018 0.02927963 0.014639817 [128,] 0.99028310 0.01943380 0.009716902 [129,] 0.98687540 0.02624921 0.013124604 [130,] 0.98731473 0.02537055 0.012685275 [131,] 0.98286115 0.03427770 0.017138852 [132,] 0.97703371 0.04593259 0.022966294 [133,] 0.97234423 0.05531154 0.027655768 [134,] 0.96365917 0.07268166 0.036340829 [135,] 0.95331829 0.09336341 0.046681705 [136,] 0.96041479 0.07917043 0.039585213 [137,] 0.94869579 0.10260843 0.051304214 [138,] 0.95865274 0.08269453 0.041347265 [139,] 0.97813014 0.04373971 0.021869855 [140,] 0.97188129 0.05623743 0.028118713 [141,] 0.96250985 0.07498031 0.037490153 [142,] 0.96113430 0.07773140 0.038865702 [143,] 0.94887399 0.10225203 0.051126013 [144,] 0.94883970 0.10232060 0.051160301 [145,] 0.94355101 0.11289798 0.056448992 [146,] 0.93574962 0.12850076 0.064250380 [147,] 0.92436886 0.15126228 0.075631139 [148,] 0.94471827 0.11056346 0.055281730 [149,] 0.92897572 0.14204856 0.071024281 [150,] 0.90887070 0.18225861 0.091129303 [151,] 0.91998746 0.16002508 0.080012538 [152,] 0.90073619 0.19852762 0.099263808 [153,] 0.87662281 0.24675439 0.123377193 [154,] 0.87392036 0.25215928 0.126079640 [155,] 0.84027070 0.31945860 0.159729302 [156,] 0.80106488 0.39787024 0.198935122 [157,] 0.78427240 0.43145520 0.215727601 [158,] 0.74352335 0.51295330 0.256476650 [159,] 0.71471558 0.57056884 0.285284422 [160,] 0.71026375 0.57947251 0.289736254 [161,] 0.75632975 0.48734049 0.243670246 [162,] 0.92857746 0.14284508 0.071422539 [163,] 0.91351054 0.17297892 0.086489458 [164,] 0.98528616 0.02942769 0.014713843 [165,] 0.98079066 0.03841868 0.019209339 [166,] 0.97301380 0.05397240 0.026986200 [167,] 0.95796438 0.08407125 0.042035623 [168,] 0.96584488 0.06831024 0.034155118 [169,] 0.94614751 0.10770499 0.053852493 [170,] 0.92849451 0.14301098 0.071505491 [171,] 0.94976319 0.10047362 0.050236810 [172,] 0.92185171 0.15629658 0.078148289 [173,] 0.87805513 0.24388974 0.121944869 [174,] 0.81786250 0.36427499 0.182137497 [175,] 0.81054533 0.37890934 0.189454672 [176,] 0.87330481 0.25339038 0.126695190 [177,] 0.80400180 0.39199640 0.195998200 [178,] 0.89332689 0.21334622 0.106673112 [179,] 0.85728126 0.28543749 0.142718745 [180,] 0.92610688 0.14778623 0.073893116 [181,] 0.84611211 0.30777578 0.153887888 > postscript(file="/var/wessaorg/rcomp/tmp/1ntgr1384974375.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/2k2of1384974375.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3l6b81384974375.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4tmkx1384974375.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5k24y1384974375.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 -189.39645069 -75.81000638 -197.16985865 127.92816485 -151.18832534 7 8 9 10 11 -25.73044958 14.54245921 -81.90802988 24.73950454 476.36857225 12 13 14 15 16 152.93485319 -240.50455587 25.99394663 -30.32797391 -158.60088270 17 18 19 20 21 -39.81739306 -105.69990453 214.50822082 27.06611675 -50.73314459 22 23 24 25 26 290.11882183 339.11612683 425.32155717 -173.75330795 -261.96712331 27 28 29 30 31 16.08827678 -78.23733709 148.57300426 -26.93388325 59.83483303 32 33 34 35 36 159.46759408 -231.39175902 338.13359519 340.35849057 145.08288677 37 38 39 40 41 59.32894385 -180.97450999 85.75158289 -223.13831526 354.14098187 42 43 44 45 46 -29.39914570 161.33902554 -186.35752063 79.32325384 220.35010555 47 48 49 50 51 514.60085430 502.09865847 -219.41930906 3.14297854 -197.07722516 52 53 54 55 56 250.00502665 143.00602498 -86.68313450 233.94493488 6.55553590 57 58 59 60 61 242.57030925 128.46489908 169.02549001 176.69987614 -385.78485134 62 63 64 65 66 -143.82477974 -31.60926771 -226.41591572 228.84860805 72.43704903 67 68 69 70 71 10.54715088 130.70995782 178.57400259 176.67671776 144.94593321 72 73 74 75 76 94.34371721 -353.41022571 -270.98020000 166.49244912 -292.99128002 77 78 79 80 81 16.84860805 -168.85163145 -85.11715356 2.43974404 50.78482295 82 83 84 85 86 -116.55187095 288.26216374 362.05134339 -552.15209028 94.59516430 87 88 89 90 91 -269.91172322 -123.15508529 19.52668752 -287.89325652 70.57939260 92 93 94 95 96 -267.33266558 160.05673340 89.01241332 221.55453756 403.12351351 97 98 99 100 101 -425.16317030 -271.43068908 -103.31419889 -117.71567622 -121.59449435 102 103 104 105 106 10.16683525 -62.49177918 47.38703895 -154.22995041 97.70895949 107 108 109 110 111 303.88384478 317.23730870 -79.39445402 -407.59619102 9.63678937 112 113 114 115 116 -159.01813173 -105.44276743 78.87915310 1.21315199 -40.19201868 117 118 119 120 121 -23.02921175 13.77004959 355.16414024 332.22992202 -252.48139750 122 123 124 125 126 -333.05506512 219.51930084 -284.40753071 3.27693710 -182.53709759 127 128 129 130 131 -106.51863089 23.04196004 32.74319788 -17.51024588 340.36857225 132 133 134 135 136 298.99494496 -365.27327215 -322.31320055 17.29171046 -221.52971091 137 138 139 140 141 -35.06814181 -25.60188103 -131.77207465 -0.08291517 -62.97650666 142 143 144 145 146 218.58408428 -50.01713339 211.59616263 -385.99397502 -103.04498344 147 148 149 150 151 -8.80261970 -200.57502932 5.76535791 -206.77207465 136.92816485 152 153 154 155 156 -157.94965495 96.90969815 244.44443571 9.92646818 -87.26319047 157 158 159 160 161 -266.36221230 -104.52232423 -86.48069916 -184.52232423 -4.26888048 162 163 164 165 166 -11.36690397 -126.81739306 113.99294829 -101.47600749 212.13728853 167 168 169 170 171 196.25946874 182.51760417 -454.33436225 -382.48283515 58.26172442 172 173 174 175 176 -94.80206068 5.20532599 -198.32471989 2.09891748 -95.63556041 177 178 179 180 181 214.76961027 90.40706300 47.99819898 80.55878992 -94.64564209 182 183 184 185 186 -186.78259565 53.12576920 -193.77151563 103.33389454 -128.37373164 187 188 189 190 191 -19.67718548 18.63734838 138.94818890 167.52455153 245.66519843 192 167.96126559 > postscript(file="/var/wessaorg/rcomp/tmp/6dg8q1384974375.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 -189.39645069 NA 1 -75.81000638 -189.39645069 2 -197.16985865 -75.81000638 3 127.92816485 -197.16985865 4 -151.18832534 127.92816485 5 -25.73044958 -151.18832534 6 14.54245921 -25.73044958 7 -81.90802988 14.54245921 8 24.73950454 -81.90802988 9 476.36857225 24.73950454 10 152.93485319 476.36857225 11 -240.50455587 152.93485319 12 25.99394663 -240.50455587 13 -30.32797391 25.99394663 14 -158.60088270 -30.32797391 15 -39.81739306 -158.60088270 16 -105.69990453 -39.81739306 17 214.50822082 -105.69990453 18 27.06611675 214.50822082 19 -50.73314459 27.06611675 20 290.11882183 -50.73314459 21 339.11612683 290.11882183 22 425.32155717 339.11612683 23 -173.75330795 425.32155717 24 -261.96712331 -173.75330795 25 16.08827678 -261.96712331 26 -78.23733709 16.08827678 27 148.57300426 -78.23733709 28 -26.93388325 148.57300426 29 59.83483303 -26.93388325 30 159.46759408 59.83483303 31 -231.39175902 159.46759408 32 338.13359519 -231.39175902 33 340.35849057 338.13359519 34 145.08288677 340.35849057 35 59.32894385 145.08288677 36 -180.97450999 59.32894385 37 85.75158289 -180.97450999 38 -223.13831526 85.75158289 39 354.14098187 -223.13831526 40 -29.39914570 354.14098187 41 161.33902554 -29.39914570 42 -186.35752063 161.33902554 43 79.32325384 -186.35752063 44 220.35010555 79.32325384 45 514.60085430 220.35010555 46 502.09865847 514.60085430 47 -219.41930906 502.09865847 48 3.14297854 -219.41930906 49 -197.07722516 3.14297854 50 250.00502665 -197.07722516 51 143.00602498 250.00502665 52 -86.68313450 143.00602498 53 233.94493488 -86.68313450 54 6.55553590 233.94493488 55 242.57030925 6.55553590 56 128.46489908 242.57030925 57 169.02549001 128.46489908 58 176.69987614 169.02549001 59 -385.78485134 176.69987614 60 -143.82477974 -385.78485134 61 -31.60926771 -143.82477974 62 -226.41591572 -31.60926771 63 228.84860805 -226.41591572 64 72.43704903 228.84860805 65 10.54715088 72.43704903 66 130.70995782 10.54715088 67 178.57400259 130.70995782 68 176.67671776 178.57400259 69 144.94593321 176.67671776 70 94.34371721 144.94593321 71 -353.41022571 94.34371721 72 -270.98020000 -353.41022571 73 166.49244912 -270.98020000 74 -292.99128002 166.49244912 75 16.84860805 -292.99128002 76 -168.85163145 16.84860805 77 -85.11715356 -168.85163145 78 2.43974404 -85.11715356 79 50.78482295 2.43974404 80 -116.55187095 50.78482295 81 288.26216374 -116.55187095 82 362.05134339 288.26216374 83 -552.15209028 362.05134339 84 94.59516430 -552.15209028 85 -269.91172322 94.59516430 86 -123.15508529 -269.91172322 87 19.52668752 -123.15508529 88 -287.89325652 19.52668752 89 70.57939260 -287.89325652 90 -267.33266558 70.57939260 91 160.05673340 -267.33266558 92 89.01241332 160.05673340 93 221.55453756 89.01241332 94 403.12351351 221.55453756 95 -425.16317030 403.12351351 96 -271.43068908 -425.16317030 97 -103.31419889 -271.43068908 98 -117.71567622 -103.31419889 99 -121.59449435 -117.71567622 100 10.16683525 -121.59449435 101 -62.49177918 10.16683525 102 47.38703895 -62.49177918 103 -154.22995041 47.38703895 104 97.70895949 -154.22995041 105 303.88384478 97.70895949 106 317.23730870 303.88384478 107 -79.39445402 317.23730870 108 -407.59619102 -79.39445402 109 9.63678937 -407.59619102 110 -159.01813173 9.63678937 111 -105.44276743 -159.01813173 112 78.87915310 -105.44276743 113 1.21315199 78.87915310 114 -40.19201868 1.21315199 115 -23.02921175 -40.19201868 116 13.77004959 -23.02921175 117 355.16414024 13.77004959 118 332.22992202 355.16414024 119 -252.48139750 332.22992202 120 -333.05506512 -252.48139750 121 219.51930084 -333.05506512 122 -284.40753071 219.51930084 123 3.27693710 -284.40753071 124 -182.53709759 3.27693710 125 -106.51863089 -182.53709759 126 23.04196004 -106.51863089 127 32.74319788 23.04196004 128 -17.51024588 32.74319788 129 340.36857225 -17.51024588 130 298.99494496 340.36857225 131 -365.27327215 298.99494496 132 -322.31320055 -365.27327215 133 17.29171046 -322.31320055 134 -221.52971091 17.29171046 135 -35.06814181 -221.52971091 136 -25.60188103 -35.06814181 137 -131.77207465 -25.60188103 138 -0.08291517 -131.77207465 139 -62.97650666 -0.08291517 140 218.58408428 -62.97650666 141 -50.01713339 218.58408428 142 211.59616263 -50.01713339 143 -385.99397502 211.59616263 144 -103.04498344 -385.99397502 145 -8.80261970 -103.04498344 146 -200.57502932 -8.80261970 147 5.76535791 -200.57502932 148 -206.77207465 5.76535791 149 136.92816485 -206.77207465 150 -157.94965495 136.92816485 151 96.90969815 -157.94965495 152 244.44443571 96.90969815 153 9.92646818 244.44443571 154 -87.26319047 9.92646818 155 -266.36221230 -87.26319047 156 -104.52232423 -266.36221230 157 -86.48069916 -104.52232423 158 -184.52232423 -86.48069916 159 -4.26888048 -184.52232423 160 -11.36690397 -4.26888048 161 -126.81739306 -11.36690397 162 113.99294829 -126.81739306 163 -101.47600749 113.99294829 164 212.13728853 -101.47600749 165 196.25946874 212.13728853 166 182.51760417 196.25946874 167 -454.33436225 182.51760417 168 -382.48283515 -454.33436225 169 58.26172442 -382.48283515 170 -94.80206068 58.26172442 171 5.20532599 -94.80206068 172 -198.32471989 5.20532599 173 2.09891748 -198.32471989 174 -95.63556041 2.09891748 175 214.76961027 -95.63556041 176 90.40706300 214.76961027 177 47.99819898 90.40706300 178 80.55878992 47.99819898 179 -94.64564209 80.55878992 180 -186.78259565 -94.64564209 181 53.12576920 -186.78259565 182 -193.77151563 53.12576920 183 103.33389454 -193.77151563 184 -128.37373164 103.33389454 185 -19.67718548 -128.37373164 186 18.63734838 -19.67718548 187 138.94818890 18.63734838 188 167.52455153 138.94818890 189 245.66519843 167.52455153 190 167.96126559 245.66519843 191 NA 167.96126559 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -75.81000638 -189.39645069 [2,] -197.16985865 -75.81000638 [3,] 127.92816485 -197.16985865 [4,] -151.18832534 127.92816485 [5,] -25.73044958 -151.18832534 [6,] 14.54245921 -25.73044958 [7,] -81.90802988 14.54245921 [8,] 24.73950454 -81.90802988 [9,] 476.36857225 24.73950454 [10,] 152.93485319 476.36857225 [11,] -240.50455587 152.93485319 [12,] 25.99394663 -240.50455587 [13,] -30.32797391 25.99394663 [14,] -158.60088270 -30.32797391 [15,] -39.81739306 -158.60088270 [16,] -105.69990453 -39.81739306 [17,] 214.50822082 -105.69990453 [18,] 27.06611675 214.50822082 [19,] -50.73314459 27.06611675 [20,] 290.11882183 -50.73314459 [21,] 339.11612683 290.11882183 [22,] 425.32155717 339.11612683 [23,] -173.75330795 425.32155717 [24,] -261.96712331 -173.75330795 [25,] 16.08827678 -261.96712331 [26,] -78.23733709 16.08827678 [27,] 148.57300426 -78.23733709 [28,] -26.93388325 148.57300426 [29,] 59.83483303 -26.93388325 [30,] 159.46759408 59.83483303 [31,] -231.39175902 159.46759408 [32,] 338.13359519 -231.39175902 [33,] 340.35849057 338.13359519 [34,] 145.08288677 340.35849057 [35,] 59.32894385 145.08288677 [36,] -180.97450999 59.32894385 [37,] 85.75158289 -180.97450999 [38,] -223.13831526 85.75158289 [39,] 354.14098187 -223.13831526 [40,] -29.39914570 354.14098187 [41,] 161.33902554 -29.39914570 [42,] -186.35752063 161.33902554 [43,] 79.32325384 -186.35752063 [44,] 220.35010555 79.32325384 [45,] 514.60085430 220.35010555 [46,] 502.09865847 514.60085430 [47,] -219.41930906 502.09865847 [48,] 3.14297854 -219.41930906 [49,] -197.07722516 3.14297854 [50,] 250.00502665 -197.07722516 [51,] 143.00602498 250.00502665 [52,] -86.68313450 143.00602498 [53,] 233.94493488 -86.68313450 [54,] 6.55553590 233.94493488 [55,] 242.57030925 6.55553590 [56,] 128.46489908 242.57030925 [57,] 169.02549001 128.46489908 [58,] 176.69987614 169.02549001 [59,] -385.78485134 176.69987614 [60,] -143.82477974 -385.78485134 [61,] -31.60926771 -143.82477974 [62,] -226.41591572 -31.60926771 [63,] 228.84860805 -226.41591572 [64,] 72.43704903 228.84860805 [65,] 10.54715088 72.43704903 [66,] 130.70995782 10.54715088 [67,] 178.57400259 130.70995782 [68,] 176.67671776 178.57400259 [69,] 144.94593321 176.67671776 [70,] 94.34371721 144.94593321 [71,] -353.41022571 94.34371721 [72,] -270.98020000 -353.41022571 [73,] 166.49244912 -270.98020000 [74,] -292.99128002 166.49244912 [75,] 16.84860805 -292.99128002 [76,] -168.85163145 16.84860805 [77,] -85.11715356 -168.85163145 [78,] 2.43974404 -85.11715356 [79,] 50.78482295 2.43974404 [80,] -116.55187095 50.78482295 [81,] 288.26216374 -116.55187095 [82,] 362.05134339 288.26216374 [83,] -552.15209028 362.05134339 [84,] 94.59516430 -552.15209028 [85,] -269.91172322 94.59516430 [86,] -123.15508529 -269.91172322 [87,] 19.52668752 -123.15508529 [88,] -287.89325652 19.52668752 [89,] 70.57939260 -287.89325652 [90,] -267.33266558 70.57939260 [91,] 160.05673340 -267.33266558 [92,] 89.01241332 160.05673340 [93,] 221.55453756 89.01241332 [94,] 403.12351351 221.55453756 [95,] -425.16317030 403.12351351 [96,] -271.43068908 -425.16317030 [97,] -103.31419889 -271.43068908 [98,] -117.71567622 -103.31419889 [99,] -121.59449435 -117.71567622 [100,] 10.16683525 -121.59449435 [101,] -62.49177918 10.16683525 [102,] 47.38703895 -62.49177918 [103,] -154.22995041 47.38703895 [104,] 97.70895949 -154.22995041 [105,] 303.88384478 97.70895949 [106,] 317.23730870 303.88384478 [107,] -79.39445402 317.23730870 [108,] -407.59619102 -79.39445402 [109,] 9.63678937 -407.59619102 [110,] -159.01813173 9.63678937 [111,] -105.44276743 -159.01813173 [112,] 78.87915310 -105.44276743 [113,] 1.21315199 78.87915310 [114,] -40.19201868 1.21315199 [115,] -23.02921175 -40.19201868 [116,] 13.77004959 -23.02921175 [117,] 355.16414024 13.77004959 [118,] 332.22992202 355.16414024 [119,] -252.48139750 332.22992202 [120,] -333.05506512 -252.48139750 [121,] 219.51930084 -333.05506512 [122,] -284.40753071 219.51930084 [123,] 3.27693710 -284.40753071 [124,] -182.53709759 3.27693710 [125,] -106.51863089 -182.53709759 [126,] 23.04196004 -106.51863089 [127,] 32.74319788 23.04196004 [128,] -17.51024588 32.74319788 [129,] 340.36857225 -17.51024588 [130,] 298.99494496 340.36857225 [131,] -365.27327215 298.99494496 [132,] -322.31320055 -365.27327215 [133,] 17.29171046 -322.31320055 [134,] -221.52971091 17.29171046 [135,] -35.06814181 -221.52971091 [136,] -25.60188103 -35.06814181 [137,] -131.77207465 -25.60188103 [138,] -0.08291517 -131.77207465 [139,] -62.97650666 -0.08291517 [140,] 218.58408428 -62.97650666 [141,] -50.01713339 218.58408428 [142,] 211.59616263 -50.01713339 [143,] -385.99397502 211.59616263 [144,] -103.04498344 -385.99397502 [145,] -8.80261970 -103.04498344 [146,] -200.57502932 -8.80261970 [147,] 5.76535791 -200.57502932 [148,] -206.77207465 5.76535791 [149,] 136.92816485 -206.77207465 [150,] -157.94965495 136.92816485 [151,] 96.90969815 -157.94965495 [152,] 244.44443571 96.90969815 [153,] 9.92646818 244.44443571 [154,] -87.26319047 9.92646818 [155,] -266.36221230 -87.26319047 [156,] -104.52232423 -266.36221230 [157,] -86.48069916 -104.52232423 [158,] -184.52232423 -86.48069916 [159,] -4.26888048 -184.52232423 [160,] -11.36690397 -4.26888048 [161,] -126.81739306 -11.36690397 [162,] 113.99294829 -126.81739306 [163,] -101.47600749 113.99294829 [164,] 212.13728853 -101.47600749 [165,] 196.25946874 212.13728853 [166,] 182.51760417 196.25946874 [167,] -454.33436225 182.51760417 [168,] -382.48283515 -454.33436225 [169,] 58.26172442 -382.48283515 [170,] -94.80206068 58.26172442 [171,] 5.20532599 -94.80206068 [172,] -198.32471989 5.20532599 [173,] 2.09891748 -198.32471989 [174,] -95.63556041 2.09891748 [175,] 214.76961027 -95.63556041 [176,] 90.40706300 214.76961027 [177,] 47.99819898 90.40706300 [178,] 80.55878992 47.99819898 [179,] -94.64564209 80.55878992 [180,] -186.78259565 -94.64564209 [181,] 53.12576920 -186.78259565 [182,] -193.77151563 53.12576920 [183,] 103.33389454 -193.77151563 [184,] -128.37373164 103.33389454 [185,] -19.67718548 -128.37373164 [186,] 18.63734838 -19.67718548 [187,] 138.94818890 18.63734838 [188,] 167.52455153 138.94818890 [189,] 245.66519843 167.52455153 [190,] 167.96126559 245.66519843 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -75.81000638 -189.39645069 2 -197.16985865 -75.81000638 3 127.92816485 -197.16985865 4 -151.18832534 127.92816485 5 -25.73044958 -151.18832534 6 14.54245921 -25.73044958 7 -81.90802988 14.54245921 8 24.73950454 -81.90802988 9 476.36857225 24.73950454 10 152.93485319 476.36857225 11 -240.50455587 152.93485319 12 25.99394663 -240.50455587 13 -30.32797391 25.99394663 14 -158.60088270 -30.32797391 15 -39.81739306 -158.60088270 16 -105.69990453 -39.81739306 17 214.50822082 -105.69990453 18 27.06611675 214.50822082 19 -50.73314459 27.06611675 20 290.11882183 -50.73314459 21 339.11612683 290.11882183 22 425.32155717 339.11612683 23 -173.75330795 425.32155717 24 -261.96712331 -173.75330795 25 16.08827678 -261.96712331 26 -78.23733709 16.08827678 27 148.57300426 -78.23733709 28 -26.93388325 148.57300426 29 59.83483303 -26.93388325 30 159.46759408 59.83483303 31 -231.39175902 159.46759408 32 338.13359519 -231.39175902 33 340.35849057 338.13359519 34 145.08288677 340.35849057 35 59.32894385 145.08288677 36 -180.97450999 59.32894385 37 85.75158289 -180.97450999 38 -223.13831526 85.75158289 39 354.14098187 -223.13831526 40 -29.39914570 354.14098187 41 161.33902554 -29.39914570 42 -186.35752063 161.33902554 43 79.32325384 -186.35752063 44 220.35010555 79.32325384 45 514.60085430 220.35010555 46 502.09865847 514.60085430 47 -219.41930906 502.09865847 48 3.14297854 -219.41930906 49 -197.07722516 3.14297854 50 250.00502665 -197.07722516 51 143.00602498 250.00502665 52 -86.68313450 143.00602498 53 233.94493488 -86.68313450 54 6.55553590 233.94493488 55 242.57030925 6.55553590 56 128.46489908 242.57030925 57 169.02549001 128.46489908 58 176.69987614 169.02549001 59 -385.78485134 176.69987614 60 -143.82477974 -385.78485134 61 -31.60926771 -143.82477974 62 -226.41591572 -31.60926771 63 228.84860805 -226.41591572 64 72.43704903 228.84860805 65 10.54715088 72.43704903 66 130.70995782 10.54715088 67 178.57400259 130.70995782 68 176.67671776 178.57400259 69 144.94593321 176.67671776 70 94.34371721 144.94593321 71 -353.41022571 94.34371721 72 -270.98020000 -353.41022571 73 166.49244912 -270.98020000 74 -292.99128002 166.49244912 75 16.84860805 -292.99128002 76 -168.85163145 16.84860805 77 -85.11715356 -168.85163145 78 2.43974404 -85.11715356 79 50.78482295 2.43974404 80 -116.55187095 50.78482295 81 288.26216374 -116.55187095 82 362.05134339 288.26216374 83 -552.15209028 362.05134339 84 94.59516430 -552.15209028 85 -269.91172322 94.59516430 86 -123.15508529 -269.91172322 87 19.52668752 -123.15508529 88 -287.89325652 19.52668752 89 70.57939260 -287.89325652 90 -267.33266558 70.57939260 91 160.05673340 -267.33266558 92 89.01241332 160.05673340 93 221.55453756 89.01241332 94 403.12351351 221.55453756 95 -425.16317030 403.12351351 96 -271.43068908 -425.16317030 97 -103.31419889 -271.43068908 98 -117.71567622 -103.31419889 99 -121.59449435 -117.71567622 100 10.16683525 -121.59449435 101 -62.49177918 10.16683525 102 47.38703895 -62.49177918 103 -154.22995041 47.38703895 104 97.70895949 -154.22995041 105 303.88384478 97.70895949 106 317.23730870 303.88384478 107 -79.39445402 317.23730870 108 -407.59619102 -79.39445402 109 9.63678937 -407.59619102 110 -159.01813173 9.63678937 111 -105.44276743 -159.01813173 112 78.87915310 -105.44276743 113 1.21315199 78.87915310 114 -40.19201868 1.21315199 115 -23.02921175 -40.19201868 116 13.77004959 -23.02921175 117 355.16414024 13.77004959 118 332.22992202 355.16414024 119 -252.48139750 332.22992202 120 -333.05506512 -252.48139750 121 219.51930084 -333.05506512 122 -284.40753071 219.51930084 123 3.27693710 -284.40753071 124 -182.53709759 3.27693710 125 -106.51863089 -182.53709759 126 23.04196004 -106.51863089 127 32.74319788 23.04196004 128 -17.51024588 32.74319788 129 340.36857225 -17.51024588 130 298.99494496 340.36857225 131 -365.27327215 298.99494496 132 -322.31320055 -365.27327215 133 17.29171046 -322.31320055 134 -221.52971091 17.29171046 135 -35.06814181 -221.52971091 136 -25.60188103 -35.06814181 137 -131.77207465 -25.60188103 138 -0.08291517 -131.77207465 139 -62.97650666 -0.08291517 140 218.58408428 -62.97650666 141 -50.01713339 218.58408428 142 211.59616263 -50.01713339 143 -385.99397502 211.59616263 144 -103.04498344 -385.99397502 145 -8.80261970 -103.04498344 146 -200.57502932 -8.80261970 147 5.76535791 -200.57502932 148 -206.77207465 5.76535791 149 136.92816485 -206.77207465 150 -157.94965495 136.92816485 151 96.90969815 -157.94965495 152 244.44443571 96.90969815 153 9.92646818 244.44443571 154 -87.26319047 9.92646818 155 -266.36221230 -87.26319047 156 -104.52232423 -266.36221230 157 -86.48069916 -104.52232423 158 -184.52232423 -86.48069916 159 -4.26888048 -184.52232423 160 -11.36690397 -4.26888048 161 -126.81739306 -11.36690397 162 113.99294829 -126.81739306 163 -101.47600749 113.99294829 164 212.13728853 -101.47600749 165 196.25946874 212.13728853 166 182.51760417 196.25946874 167 -454.33436225 182.51760417 168 -382.48283515 -454.33436225 169 58.26172442 -382.48283515 170 -94.80206068 58.26172442 171 5.20532599 -94.80206068 172 -198.32471989 5.20532599 173 2.09891748 -198.32471989 174 -95.63556041 2.09891748 175 214.76961027 -95.63556041 176 90.40706300 214.76961027 177 47.99819898 90.40706300 178 80.55878992 47.99819898 179 -94.64564209 80.55878992 180 -186.78259565 -94.64564209 181 53.12576920 -186.78259565 182 -193.77151563 53.12576920 183 103.33389454 -193.77151563 184 -128.37373164 103.33389454 185 -19.67718548 -128.37373164 186 18.63734838 -19.67718548 187 138.94818890 18.63734838 188 167.52455153 138.94818890 189 245.66519843 167.52455153 190 167.96126559 245.66519843 > 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/7blnm1384974375.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/80nib1384974375.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/9im3z1384974375.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/10bk8u1384974375.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11788t1384974375.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12u5a81384974375.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, signif(sqrt(mysum$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$sigma,6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, signif(sum(myerror*myerror),6)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13vqzh1384974375.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,signif(x[i],6)) + a<-table.element(a,signif(x[i]-mysum$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/14jqts1384974375.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/15haht1384974376.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/165su11384974376.tab") + } > > try(system("convert tmp/1ntgr1384974375.ps tmp/1ntgr1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/2k2of1384974375.ps tmp/2k2of1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/3l6b81384974375.ps tmp/3l6b81384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/4tmkx1384974375.ps tmp/4tmkx1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/5k24y1384974375.ps tmp/5k24y1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/6dg8q1384974375.ps tmp/6dg8q1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/7blnm1384974375.ps tmp/7blnm1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/80nib1384974375.ps tmp/80nib1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/9im3z1384974375.ps tmp/9im3z1384974375.png",intern=TRUE)) character(0) > try(system("convert tmp/10bk8u1384974375.ps tmp/10bk8u1384974375.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 10.817 1.695 12.492