R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1507 + ,0 + ,1508 + ,1687 + ,1385 + ,0 + ,1507 + ,1508 + ,1632 + ,0 + ,1385 + ,1507 + ,1511 + ,0 + ,1632 + ,1385 + ,1559 + ,0 + ,1511 + ,1632 + ,1630 + ,0 + ,1559 + ,1511 + ,1579 + ,0 + ,1630 + ,1559 + ,1653 + ,0 + ,1579 + ,1630 + ,2152 + ,0 + ,1653 + ,1579 + ,2148 + ,0 + ,2152 + ,1653 + ,1752 + ,0 + ,2148 + ,2152 + ,1765 + ,0 + ,1752 + ,2148 + ,1717 + ,0 + ,1765 + ,1752 + ,1558 + ,0 + ,1717 + ,1765 + ,1575 + ,0 + ,1558 + ,1717 + ,1520 + ,0 + ,1575 + ,1558 + ,1805 + ,0 + ,1520 + ,1575 + ,1800 + ,0 + ,1805 + ,1520 + ,1719 + ,0 + ,1800 + ,1805 + ,2008 + ,0 + ,1719 + ,1800 + ,2242 + ,0 + ,2008 + ,1719 + ,2478 + ,0 + ,2242 + ,2008 + ,2030 + ,0 + ,2478 + ,2242 + ,1655 + ,0 + ,2030 + ,2478 + ,1693 + ,0 + ,1655 + ,2030 + ,1623 + ,0 + ,1693 + ,1655 + ,1805 + ,0 + ,1623 + ,1693 + ,1746 + ,0 + ,1805 + ,1623 + ,1795 + ,0 + ,1746 + ,1805 + ,1926 + ,0 + ,1795 + ,1746 + ,1619 + ,0 + ,1926 + ,1795 + ,1992 + ,0 + ,1619 + ,1926 + ,2233 + ,0 + ,1992 + ,1619 + 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+ ,1076 + ,1 + ,1236 + ,1168 + ,1174 + ,1 + ,1076 + ,1236 + ,1139 + ,1 + ,1174 + ,1076 + ,1427 + ,1 + ,1139 + ,1174 + ,1487 + ,1 + ,1427 + ,1139 + ,1483 + ,1 + ,1487 + ,1427 + ,1513 + ,1 + ,1483 + ,1487 + ,1357 + ,1 + ,1513 + ,1483 + ,1165 + ,1 + ,1357 + ,1513 + ,1282 + ,1 + ,1165 + ,1357 + ,1110 + ,1 + ,1282 + ,1165 + ,1297 + ,1 + ,1110 + ,1282 + ,1185 + ,1 + ,1297 + ,1110 + ,1222 + ,1 + ,1185 + ,1297 + ,1284 + ,1 + ,1222 + ,1185 + ,1444 + ,1 + ,1284 + ,1222 + ,1575 + ,1 + ,1444 + ,1284 + ,1737 + ,1 + ,1575 + ,1444 + ,1763 + ,1 + ,1737 + ,1575) + ,dim=c(4 + ,190) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2') + ,1:190)) > y <- array(NA,dim=c(4,190),dimnames=list(c('Y','X','Y1','Y2'),1:190)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Y X Y1 Y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 1507 0 1508 1687 1 0 0 0 0 0 0 0 0 0 0 1 2 1385 0 1507 1508 0 1 0 0 0 0 0 0 0 0 0 2 3 1632 0 1385 1507 0 0 1 0 0 0 0 0 0 0 0 3 4 1511 0 1632 1385 0 0 0 1 0 0 0 0 0 0 0 4 5 1559 0 1511 1632 0 0 0 0 1 0 0 0 0 0 0 5 6 1630 0 1559 1511 0 0 0 0 0 1 0 0 0 0 0 6 7 1579 0 1630 1559 0 0 0 0 0 0 1 0 0 0 0 7 8 1653 0 1579 1630 0 0 0 0 0 0 0 1 0 0 0 8 9 2152 0 1653 1579 0 0 0 0 0 0 0 0 1 0 0 9 10 2148 0 2152 1653 0 0 0 0 0 0 0 0 0 1 0 10 11 1752 0 2148 2152 0 0 0 0 0 0 0 0 0 0 1 11 12 1765 0 1752 2148 0 0 0 0 0 0 0 0 0 0 0 12 13 1717 0 1765 1752 1 0 0 0 0 0 0 0 0 0 0 13 14 1558 0 1717 1765 0 1 0 0 0 0 0 0 0 0 0 14 15 1575 0 1558 1717 0 0 1 0 0 0 0 0 0 0 0 15 16 1520 0 1575 1558 0 0 0 1 0 0 0 0 0 0 0 16 17 1805 0 1520 1575 0 0 0 0 1 0 0 0 0 0 0 17 18 1800 0 1805 1520 0 0 0 0 0 1 0 0 0 0 0 18 19 1719 0 1800 1805 0 0 0 0 0 0 1 0 0 0 0 19 20 2008 0 1719 1800 0 0 0 0 0 0 0 1 0 0 0 20 21 2242 0 2008 1719 0 0 0 0 0 0 0 0 1 0 0 21 22 2478 0 2242 2008 0 0 0 0 0 0 0 0 0 1 0 22 23 2030 0 2478 2242 0 0 0 0 0 0 0 0 0 0 1 23 24 1655 0 2030 2478 0 0 0 0 0 0 0 0 0 0 0 24 25 1693 0 1655 2030 1 0 0 0 0 0 0 0 0 0 0 25 26 1623 0 1693 1655 0 1 0 0 0 0 0 0 0 0 0 26 27 1805 0 1623 1693 0 0 1 0 0 0 0 0 0 0 0 27 28 1746 0 1805 1623 0 0 0 1 0 0 0 0 0 0 0 28 29 1795 0 1746 1805 0 0 0 0 1 0 0 0 0 0 0 29 30 1926 0 1795 1746 0 0 0 0 0 1 0 0 0 0 0 30 31 1619 0 1926 1795 0 0 0 0 0 0 1 0 0 0 0 31 32 1992 0 1619 1926 0 0 0 0 0 0 0 1 0 0 0 32 33 2233 0 1992 1619 0 0 0 0 0 0 0 0 1 0 0 33 34 2192 0 2233 1992 0 0 0 0 0 0 0 0 0 1 0 34 35 2080 0 2192 2233 0 0 0 0 0 0 0 0 0 0 1 35 36 1768 0 2080 2192 0 0 0 0 0 0 0 0 0 0 0 36 37 1835 0 1768 2080 1 0 0 0 0 0 0 0 0 0 0 37 38 1569 0 1835 1768 0 1 0 0 0 0 0 0 0 0 0 38 39 1976 0 1569 1835 0 0 1 0 0 0 0 0 0 0 0 39 40 1853 0 1976 1569 0 0 0 1 0 0 0 0 0 0 0 40 41 1965 0 1853 1976 0 0 0 0 1 0 0 0 0 0 0 41 42 1689 0 1965 1853 0 0 0 0 0 1 0 0 0 0 0 42 43 1778 0 1689 1965 0 0 0 0 0 0 1 0 0 0 0 43 44 1976 0 1778 1689 0 0 0 0 0 0 0 1 0 0 0 44 45 2397 0 1976 1778 0 0 0 0 0 0 0 0 1 0 0 45 46 2654 0 2397 1976 0 0 0 0 0 0 0 0 0 1 0 46 47 2097 0 2654 2397 0 0 0 0 0 0 0 0 0 0 1 47 48 1963 0 2097 2654 0 0 0 0 0 0 0 0 0 0 0 48 49 1677 0 1963 2097 1 0 0 0 0 0 0 0 0 0 0 49 50 1941 0 1677 1963 0 1 0 0 0 0 0 0 0 0 0 50 51 2003 0 1941 1677 0 0 1 0 0 0 0 0 0 0 0 51 52 1813 0 2003 1941 0 0 0 1 0 0 0 0 0 0 0 52 53 2012 0 1813 2003 0 0 0 0 1 0 0 0 0 0 0 53 54 1912 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0 1827 1548 0 0 0 0 0 0 0 0 1 0 0 141 142 1941 0 1737 1827 0 0 0 0 0 0 0 0 0 1 0 142 143 1474 0 1941 1737 0 0 0 0 0 0 0 0 0 0 1 143 144 1458 0 1474 1941 0 0 0 0 0 0 0 0 0 0 0 144 145 1542 0 1458 1474 1 0 0 0 0 0 0 0 0 0 0 145 146 1404 0 1542 1458 0 1 0 0 0 0 0 0 0 0 0 146 147 1522 0 1404 1542 0 0 1 0 0 0 0 0 0 0 0 147 148 1385 0 1522 1404 0 0 0 1 0 0 0 0 0 0 0 148 149 1641 0 1385 1522 0 0 0 0 1 0 0 0 0 0 0 149 150 1510 0 1641 1385 0 0 0 0 0 1 0 0 0 0 0 150 151 1681 0 1510 1641 0 0 0 0 0 0 1 0 0 0 0 151 152 1938 0 1681 1510 0 0 0 0 0 0 0 1 0 0 0 152 153 1868 0 1938 1681 0 0 0 0 0 0 0 0 1 0 0 153 154 1726 0 1868 1938 0 0 0 0 0 0 0 0 0 1 0 154 155 1456 0 1726 1868 0 0 0 0 0 0 0 0 0 0 1 155 156 1445 0 1456 1726 0 0 0 0 0 0 0 0 0 0 0 156 157 1456 0 1445 1456 1 0 0 0 0 0 0 0 0 0 0 157 158 1365 0 1456 1445 0 1 0 0 0 0 0 0 0 0 0 158 159 1487 0 1365 1456 0 0 1 0 0 0 0 0 0 0 0 159 160 1558 0 1487 1365 0 0 0 1 0 0 0 0 0 0 0 160 161 1488 0 1558 1487 0 0 0 0 1 0 0 0 0 0 0 161 162 1684 0 1488 1558 0 0 0 0 0 1 0 0 0 0 0 162 163 1594 0 1684 1488 0 0 0 0 0 0 1 0 0 0 0 163 164 1850 0 1594 1684 0 0 0 0 0 0 0 1 0 0 0 164 165 1998 0 1850 1594 0 0 0 0 0 0 0 0 1 0 0 165 166 2079 0 1998 1850 0 0 0 0 0 0 0 0 0 1 0 166 167 1494 0 2079 1998 0 0 0 0 0 0 0 0 0 0 1 167 168 1057 1 1494 2079 0 0 0 0 0 0 0 0 0 0 0 168 169 1218 1 1057 1494 1 0 0 0 0 0 0 0 0 0 0 169 170 1168 1 1218 1057 0 1 0 0 0 0 0 0 0 0 0 170 171 1236 1 1168 1218 0 0 1 0 0 0 0 0 0 0 0 171 172 1076 1 1236 1168 0 0 0 1 0 0 0 0 0 0 0 172 173 1174 1 1076 1236 0 0 0 0 1 0 0 0 0 0 0 173 174 1139 1 1174 1076 0 0 0 0 0 1 0 0 0 0 0 174 175 1427 1 1139 1174 0 0 0 0 0 0 1 0 0 0 0 175 176 1487 1 1427 1139 0 0 0 0 0 0 0 1 0 0 0 176 177 1483 1 1487 1427 0 0 0 0 0 0 0 0 1 0 0 177 178 1513 1 1483 1487 0 0 0 0 0 0 0 0 0 1 0 178 179 1357 1 1513 1483 0 0 0 0 0 0 0 0 0 0 1 179 180 1165 1 1357 1513 0 0 0 0 0 0 0 0 0 0 0 180 181 1282 1 1165 1357 1 0 0 0 0 0 0 0 0 0 0 181 182 1110 1 1282 1165 0 1 0 0 0 0 0 0 0 0 0 182 183 1297 1 1110 1282 0 0 1 0 0 0 0 0 0 0 0 183 184 1185 1 1297 1110 0 0 0 1 0 0 0 0 0 0 0 184 185 1222 1 1185 1297 0 0 0 0 1 0 0 0 0 0 0 185 186 1284 1 1222 1185 0 0 0 0 0 1 0 0 0 0 0 186 187 1444 1 1284 1222 0 0 0 0 0 0 1 0 0 0 0 187 188 1575 1 1444 1284 0 0 0 0 0 0 0 1 0 0 0 188 189 1737 1 1575 1444 0 0 0 0 0 0 0 0 1 0 0 189 190 1763 1 1737 1575 0 0 0 0 0 0 0 0 0 1 0 190 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 M1 M2 432.6740 -85.6152 0.4123 0.2087 221.7085 130.1641 M3 M4 M5 M6 M7 M8 304.3217 216.3298 287.0120 283.0861 314.7176 429.9532 M9 M10 M11 t 561.7713 567.7695 38.9219 -0.7380 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -335.444 -91.096 -1.289 85.222 313.936 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 432.67402 157.02555 2.755 0.00649 ** X -85.61519 37.53598 -2.281 0.02377 * Y1 0.41225 0.07423 5.554 1.03e-07 *** Y2 0.20875 0.07334 2.846 0.00495 ** M1 221.70845 53.51067 4.143 5.34e-05 *** M2 130.16410 62.33018 2.088 0.03823 * M3 304.32166 58.79007 5.176 6.19e-07 *** M4 216.32977 65.82042 3.287 0.00123 ** M5 287.01204 58.27794 4.925 1.95e-06 *** M6 283.08605 61.98534 4.567 9.33e-06 *** M7 314.71759 58.64146 5.367 2.53e-07 *** M8 429.95325 59.01186 7.286 1.07e-11 *** M9 561.77128 60.37181 9.305 < 2e-16 *** M10 567.76945 61.58903 9.219 < 2e-16 *** M11 38.92187 59.89609 0.650 0.51666 t -0.73795 0.23971 -3.078 0.00242 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 126.8 on 174 degrees of freedom Multiple R-squared: 0.8251, Adjusted R-squared: 0.81 F-statistic: 54.71 on 15 and 174 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,] 0.2837474 0.5674947905 0.7162526047 [2,] 0.4438423 0.8876845967 0.5561577016 [3,] 0.3413175 0.6826350357 0.6586824822 [4,] 0.4119831 0.8239661852 0.5880169074 [5,] 0.3366149 0.6732298475 0.6633850763 [6,] 0.4308048 0.8616096689 0.5691951655 [7,] 0.3837439 0.7674878380 0.6162560810 [8,] 0.3247392 0.6494783205 0.6752608398 [9,] 0.2435779 0.4871557947 0.7564221026 [10,] 0.1775834 0.3551668241 0.8224165879 [11,] 0.1406328 0.2812655030 0.8593672485 [12,] 0.1018587 0.2037174080 0.8981412960 [13,] 0.1936480 0.3872960750 0.8063519625 [14,] 0.1434814 0.2869628361 0.8565185820 [15,] 0.1420717 0.2841434793 0.8579282604 [16,] 0.2416082 0.4832164796 0.7583917602 [17,] 0.2284588 0.4569176126 0.7715411937 [18,] 0.1922849 0.3845697406 0.8077151297 [19,] 0.1481663 0.2963326821 0.8518336589 [20,] 0.1441327 0.2882653295 0.8558673352 [21,] 0.1573498 0.3146995973 0.8426502014 [22,] 0.1325853 0.2651706834 0.8674146583 [23,] 0.1056907 0.2113813739 0.8943093131 [24,] 0.2339885 0.4679770324 0.7660114838 [25,] 0.1935894 0.3871788223 0.8064105888 [26,] 0.1615964 0.3231927612 0.8384036194 [27,] 0.1543147 0.3086294640 0.8456852680 [28,] 0.2404136 0.4808271114 0.7595864443 [29,] 0.2077959 0.4155918816 0.7922040592 [30,] 0.1900846 0.3801692956 0.8099153522 [31,] 0.2754419 0.5508838673 0.7245580663 [32,] 0.3792643 0.7585286042 0.6207356979 [33,] 0.3706347 0.7412693679 0.6293653160 [34,] 0.3323260 0.6646519655 0.6676740173 [35,] 0.3292921 0.6585841337 0.6707079332 [36,] 0.2985664 0.5971328522 0.7014335739 [37,] 0.3663700 0.7327400743 0.6336299628 [38,] 0.3280344 0.6560688011 0.6719655995 [39,] 0.5673338 0.8653323318 0.4326661659 [40,] 0.8063170 0.3873659081 0.1936829540 [41,] 0.9309329 0.1381342393 0.0690671197 [42,] 0.9230418 0.1539163869 0.0769581935 [43,] 0.9043442 0.1913115620 0.0956557810 [44,] 0.8987146 0.2025707954 0.1012853977 [45,] 0.8966098 0.2067804132 0.1033902066 [46,] 0.9210145 0.1579710866 0.0789855433 [47,] 0.9162243 0.1675514625 0.0837757313 [48,] 0.9205827 0.1588345797 0.0794172899 [49,] 0.9469445 0.1061109397 0.0530554699 [50,] 0.9512110 0.0975780779 0.0487890390 [51,] 0.9691176 0.0617648625 0.0308824312 [52,] 0.9775432 0.0449136068 0.0224568034 [53,] 0.9782845 0.0434309107 0.0217154554 [54,] 0.9771670 0.0456659741 0.0228329871 [55,] 0.9819476 0.0361047134 0.0180523567 [56,] 0.9795138 0.0409723245 0.0204861623 [57,] 0.9783364 0.0433271084 0.0216635542 [58,] 0.9741632 0.0516735102 0.0258367551 [59,] 0.9730731 0.0538538965 0.0269269483 [60,] 0.9651863 0.0696274806 0.0348137403 [61,] 0.9580767 0.0838465739 0.0419232870 [62,] 0.9767145 0.0465710331 0.0232855166 [63,] 0.9699720 0.0600559230 0.0300279615 [64,] 0.9734159 0.0531682248 0.0265841124 [65,] 0.9840884 0.0318232011 0.0159116005 [66,] 0.9915562 0.0168875589 0.0084437795 [67,] 0.9932283 0.0135433572 0.0067716786 [68,] 0.9907740 0.0184519540 0.0092259770 [69,] 0.9877728 0.0244544444 0.0122272222 [70,] 0.9914322 0.0171356373 0.0085678186 [71,] 0.9885424 0.0229151877 0.0114575939 [72,] 0.9950062 0.0099876112 0.0049938056 [73,] 0.9943311 0.0113377227 0.0056688613 [74,] 0.9932675 0.0134649937 0.0067324968 [75,] 0.9909865 0.0180269996 0.0090134998 [76,] 0.9936320 0.0127360811 0.0063680406 [77,] 0.9922934 0.0154132635 0.0077066317 [78,] 0.9913249 0.0173502977 0.0086751488 [79,] 0.9918519 0.0162962881 0.0081481441 [80,] 0.9894616 0.0210768963 0.0105384481 [81,] 0.9914413 0.0171173317 0.0085586659 [82,] 0.9895171 0.0209658769 0.0104829385 [83,] 0.9865729 0.0268542644 0.0134271322 [84,] 0.9831473 0.0337053477 0.0168526738 [85,] 0.9874660 0.0250680878 0.0125340439 [86,] 0.9861259 0.0277482975 0.0138741487 [87,] 0.9821297 0.0357406120 0.0178703060 [88,] 0.9808913 0.0382174973 0.0191087487 [89,] 0.9937194 0.0125612715 0.0062806358 [90,] 0.9932421 0.0135157964 0.0067578982 [91,] 0.9906920 0.0186160846 0.0093080423 [92,] 0.9875689 0.0248622313 0.0124311156 [93,] 0.9880623 0.0238754851 0.0119377426 [94,] 0.9899735 0.0200530624 0.0100265312 [95,] 0.9876521 0.0246957741 0.0123478871 [96,] 0.9835773 0.0328454419 0.0164227210 [97,] 0.9785503 0.0428993287 0.0214496644 [98,] 0.9799728 0.0400543879 0.0200271939 [99,] 0.9805463 0.0389074644 0.0194537322 [100,] 0.9890929 0.0218141034 0.0109070517 [101,] 0.9928149 0.0143702827 0.0071851414 [102,] 0.9908858 0.0182283467 0.0091141733 [103,] 0.9974868 0.0050264565 0.0025132282 [104,] 0.9965443 0.0069113437 0.0034556719 [105,] 0.9958361 0.0083277639 0.0041638820 [106,] 0.9941917 0.0116166120 0.0058083060 [107,] 0.9927394 0.0145212861 0.0072606431 [108,] 0.9901772 0.0196455905 0.0098227953 [109,] 0.9870060 0.0259879657 0.0129939828 [110,] 0.9897325 0.0205349788 0.0102674894 [111,] 0.9925597 0.0148806648 0.0074403324 [112,] 0.9988990 0.0022020946 0.0011010473 [113,] 0.9996273 0.0007454266 0.0003727133 [114,] 0.9994382 0.0011235649 0.0005617825 [115,] 0.9991741 0.0016518791 0.0008259395 [116,] 0.9986951 0.0026098581 0.0013049290 [117,] 0.9979860 0.0040279563 0.0020139781 [118,] 0.9983339 0.0033321846 0.0016660923 [119,] 0.9974875 0.0050250131 0.0025125065 [120,] 0.9967998 0.0064003702 0.0032001851 [121,] 0.9953651 0.0092697438 0.0046348719 [122,] 0.9938825 0.0122350091 0.0061175046 [123,] 0.9947800 0.0104399779 0.0052199889 [124,] 0.9941262 0.0117476811 0.0058738406 [125,] 0.9910618 0.0178764070 0.0089382035 [126,] 0.9893243 0.0213513251 0.0106756626 [127,] 0.9864675 0.0270650644 0.0135325322 [128,] 0.9810203 0.0379593891 0.0189796946 [129,] 0.9733474 0.0533052239 0.0266526119 [130,] 0.9627476 0.0745048283 0.0372524141 [131,] 0.9815225 0.0369550004 0.0184775002 [132,] 0.9727003 0.0545993118 0.0272996559 [133,] 0.9666744 0.0666511315 0.0333255657 [134,] 0.9842507 0.0314986651 0.0157493325 [135,] 0.9797351 0.0405297981 0.0202648991 [136,] 0.9888918 0.0222164359 0.0111082180 [137,] 0.9843895 0.0312210207 0.0156105104 [138,] 0.9766782 0.0466435676 0.0233217838 [139,] 0.9707602 0.0584796554 0.0292398277 [140,] 0.9655430 0.0689139036 0.0344569518 [141,] 0.9657919 0.0684162666 0.0342081333 [142,] 0.9523013 0.0953973029 0.0476986514 [143,] 0.9261498 0.1477004686 0.0738502343 [144,] 0.9397457 0.1205086436 0.0602543218 [145,] 0.9468973 0.1062054489 0.0531027245 [146,] 0.9149152 0.1701696449 0.0850848225 [147,] 0.8746593 0.2506814257 0.1253407128 [148,] 0.9700296 0.0599407775 0.0299703887 [149,] 0.9412070 0.1175859200 0.0587929600 [150,] 0.8941077 0.2117846995 0.1058923497 [151,] 0.8344948 0.3310104114 0.1655052057 [152,] 0.8478285 0.3043429395 0.1521714698 [153,] 0.7095157 0.5809685091 0.2904842546 > postscript(file="/var/www/html/rcomp/tmp/1dk3n1258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/29a0c1258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3k9f31258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/48lc11258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5xckn1258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 190 Frequency = 1 1 2 3 4 5 6 -120.4826249 -112.4220145 11.6620864 -96.9674036 -120.5899857 -39.4556096 7 8 9 10 11 12 -160.6391667 -194.9330993 153.1262367 -77.2960547 -46.2272000 170.5201257 13 14 15 16 17 18 -21.1451158 -70.7883619 -151.6396726 -91.7270782 142.4538314 36.1066287 19 20 21 22 23 24 -133.2191241 75.7194726 76.4067064 150.3506644 85.7970591 -114.1181490 25 26 27 28 29 30 -48.9739713 35.9235216 65.4292181 34.7412837 0.1276429 127.9073344 31 32 33 34 35 36 -274.2202000 83.4979092 103.7330706 -119.7436542 264.4358030 46.8267560 37 38 39 40 41 42 44.8593194 -91.3497278 237.9039975 91.3737373 99.1758416 -192.6565283 43 44 45 46 47 48 -44.1479426 60.2784539 249.9934743 286.8421185 65.5951422 147.2318726 49 50 51 52 53 54 -188.2234891 313.9357568 153.3833194 -28.5562847 165.8851891 28.1729131 55 56 57 58 59 60 168.9636759 0.4332030 -126.9026647 -114.9935379 -148.5325855 2.8888363 61 62 63 64 65 66 -16.6531191 -87.0036011 147.6172188 194.1227912 4.7041073 111.2146985 67 68 69 70 71 72 156.7639257 44.4876447 -126.1105777 -193.7932772 -124.4365726 -101.8097413 73 74 75 76 77 78 163.2748210 -90.3364964 -77.2372500 -86.6239865 -123.7660291 -6.3020246 79 80 81 82 83 84 29.7830239 -247.3829996 -18.8875868 147.8680231 -241.5586801 218.0252352 85 86 87 88 89 90 -174.4237687 -29.8948143 -11.5976583 -197.0170989 12.9655747 -224.6960546 91 92 93 94 95 96 81.1503553 5.5175344 -28.0699162 170.8379454 -99.6859914 -114.9199323 97 98 99 100 101 102 -93.3869409 38.3338016 -142.8752692 77.2348430 -34.7747158 55.2888386 103 104 105 106 107 108 -152.6839307 -68.4192709 72.1373635 116.5298800 232.7249452 -159.7225060 109 110 111 112 113 114 -21.9736639 27.7929561 -136.8358976 154.9631226 50.1758690 -15.3288735 115 116 117 118 119 120 -40.6958525 -113.2885989 105.0974292 152.1901024 68.7669871 -118.7259940 121 122 123 124 125 126 222.7411560 -39.8414057 -60.3460177 -72.9468790 -115.1906158 44.2159538 127 128 129 130 131 132 52.8011253 -117.7227854 91.9029607 126.3246134 -40.6061764 -121.3758269 133 134 135 136 137 138 41.1207255 -8.9141097 -59.4132543 90.4543153 -89.3491624 18.4708449 139 140 141 142 143 144 -41.4076651 105.5387468 -229.7251453 -52.1234648 -54.8503104 118.7472681 145 146 147 148 149 150 85.8585577 8.8515266 -7.2119665 -75.3207332 142.5813514 -60.6930824 151 152 153 154 155 156 79.9788621 179.3318584 -163.3935042 -335.4444245 -2.7064303 166.9042614 157 158 159 160 161 162 17.8307521 16.8745046 0.6737509 129.1047715 -65.5769314 149.1236085 163 164 165 166 167 168 -37.9593064 99.7310492 29.9013986 -8.8121028 -128.5139641 -215.9791300 169 170 171 172 173 174 26.3233808 93.4560860 -24.9594062 -113.8253841 -34.0040178 -71.3411257 175 176 177 178 179 180 179.7367767 13.8161848 -206.1187970 -192.2549387 169.7979743 75.5069241 181 182 183 184 185 186 83.2539814 -4.6176220 55.4468012 -9.0100162 -34.8179496 39.9724783 187 188 189 190 135.7954432 73.3946971 16.9095519 -56.4818925 > postscript(file="/var/www/html/rcomp/tmp/6btt21258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 190 Frequency = 1 lag(myerror, k = 1) myerror 0 -120.4826249 NA 1 -112.4220145 -120.4826249 2 11.6620864 -112.4220145 3 -96.9674036 11.6620864 4 -120.5899857 -96.9674036 5 -39.4556096 -120.5899857 6 -160.6391667 -39.4556096 7 -194.9330993 -160.6391667 8 153.1262367 -194.9330993 9 -77.2960547 153.1262367 10 -46.2272000 -77.2960547 11 170.5201257 -46.2272000 12 -21.1451158 170.5201257 13 -70.7883619 -21.1451158 14 -151.6396726 -70.7883619 15 -91.7270782 -151.6396726 16 142.4538314 -91.7270782 17 36.1066287 142.4538314 18 -133.2191241 36.1066287 19 75.7194726 -133.2191241 20 76.4067064 75.7194726 21 150.3506644 76.4067064 22 85.7970591 150.3506644 23 -114.1181490 85.7970591 24 -48.9739713 -114.1181490 25 35.9235216 -48.9739713 26 65.4292181 35.9235216 27 34.7412837 65.4292181 28 0.1276429 34.7412837 29 127.9073344 0.1276429 30 -274.2202000 127.9073344 31 83.4979092 -274.2202000 32 103.7330706 83.4979092 33 -119.7436542 103.7330706 34 264.4358030 -119.7436542 35 46.8267560 264.4358030 36 44.8593194 46.8267560 37 -91.3497278 44.8593194 38 237.9039975 -91.3497278 39 91.3737373 237.9039975 40 99.1758416 91.3737373 41 -192.6565283 99.1758416 42 -44.1479426 -192.6565283 43 60.2784539 -44.1479426 44 249.9934743 60.2784539 45 286.8421185 249.9934743 46 65.5951422 286.8421185 47 147.2318726 65.5951422 48 -188.2234891 147.2318726 49 313.9357568 -188.2234891 50 153.3833194 313.9357568 51 -28.5562847 153.3833194 52 165.8851891 -28.5562847 53 28.1729131 165.8851891 54 168.9636759 28.1729131 55 0.4332030 168.9636759 56 -126.9026647 0.4332030 57 -114.9935379 -126.9026647 58 -148.5325855 -114.9935379 59 2.8888363 -148.5325855 60 -16.6531191 2.8888363 61 -87.0036011 -16.6531191 62 147.6172188 -87.0036011 63 194.1227912 147.6172188 64 4.7041073 194.1227912 65 111.2146985 4.7041073 66 156.7639257 111.2146985 67 44.4876447 156.7639257 68 -126.1105777 44.4876447 69 -193.7932772 -126.1105777 70 -124.4365726 -193.7932772 71 -101.8097413 -124.4365726 72 163.2748210 -101.8097413 73 -90.3364964 163.2748210 74 -77.2372500 -90.3364964 75 -86.6239865 -77.2372500 76 -123.7660291 -86.6239865 77 -6.3020246 -123.7660291 78 29.7830239 -6.3020246 79 -247.3829996 29.7830239 80 -18.8875868 -247.3829996 81 147.8680231 -18.8875868 82 -241.5586801 147.8680231 83 218.0252352 -241.5586801 84 -174.4237687 218.0252352 85 -29.8948143 -174.4237687 86 -11.5976583 -29.8948143 87 -197.0170989 -11.5976583 88 12.9655747 -197.0170989 89 -224.6960546 12.9655747 90 81.1503553 -224.6960546 91 5.5175344 81.1503553 92 -28.0699162 5.5175344 93 170.8379454 -28.0699162 94 -99.6859914 170.8379454 95 -114.9199323 -99.6859914 96 -93.3869409 -114.9199323 97 38.3338016 -93.3869409 98 -142.8752692 38.3338016 99 77.2348430 -142.8752692 100 -34.7747158 77.2348430 101 55.2888386 -34.7747158 102 -152.6839307 55.2888386 103 -68.4192709 -152.6839307 104 72.1373635 -68.4192709 105 116.5298800 72.1373635 106 232.7249452 116.5298800 107 -159.7225060 232.7249452 108 -21.9736639 -159.7225060 109 27.7929561 -21.9736639 110 -136.8358976 27.7929561 111 154.9631226 -136.8358976 112 50.1758690 154.9631226 113 -15.3288735 50.1758690 114 -40.6958525 -15.3288735 115 -113.2885989 -40.6958525 116 105.0974292 -113.2885989 117 152.1901024 105.0974292 118 68.7669871 152.1901024 119 -118.7259940 68.7669871 120 222.7411560 -118.7259940 121 -39.8414057 222.7411560 122 -60.3460177 -39.8414057 123 -72.9468790 -60.3460177 124 -115.1906158 -72.9468790 125 44.2159538 -115.1906158 126 52.8011253 44.2159538 127 -117.7227854 52.8011253 128 91.9029607 -117.7227854 129 126.3246134 91.9029607 130 -40.6061764 126.3246134 131 -121.3758269 -40.6061764 132 41.1207255 -121.3758269 133 -8.9141097 41.1207255 134 -59.4132543 -8.9141097 135 90.4543153 -59.4132543 136 -89.3491624 90.4543153 137 18.4708449 -89.3491624 138 -41.4076651 18.4708449 139 105.5387468 -41.4076651 140 -229.7251453 105.5387468 141 -52.1234648 -229.7251453 142 -54.8503104 -52.1234648 143 118.7472681 -54.8503104 144 85.8585577 118.7472681 145 8.8515266 85.8585577 146 -7.2119665 8.8515266 147 -75.3207332 -7.2119665 148 142.5813514 -75.3207332 149 -60.6930824 142.5813514 150 79.9788621 -60.6930824 151 179.3318584 79.9788621 152 -163.3935042 179.3318584 153 -335.4444245 -163.3935042 154 -2.7064303 -335.4444245 155 166.9042614 -2.7064303 156 17.8307521 166.9042614 157 16.8745046 17.8307521 158 0.6737509 16.8745046 159 129.1047715 0.6737509 160 -65.5769314 129.1047715 161 149.1236085 -65.5769314 162 -37.9593064 149.1236085 163 99.7310492 -37.9593064 164 29.9013986 99.7310492 165 -8.8121028 29.9013986 166 -128.5139641 -8.8121028 167 -215.9791300 -128.5139641 168 26.3233808 -215.9791300 169 93.4560860 26.3233808 170 -24.9594062 93.4560860 171 -113.8253841 -24.9594062 172 -34.0040178 -113.8253841 173 -71.3411257 -34.0040178 174 179.7367767 -71.3411257 175 13.8161848 179.7367767 176 -206.1187970 13.8161848 177 -192.2549387 -206.1187970 178 169.7979743 -192.2549387 179 75.5069241 169.7979743 180 83.2539814 75.5069241 181 -4.6176220 83.2539814 182 55.4468012 -4.6176220 183 -9.0100162 55.4468012 184 -34.8179496 -9.0100162 185 39.9724783 -34.8179496 186 135.7954432 39.9724783 187 73.3946971 135.7954432 188 16.9095519 73.3946971 189 -56.4818925 16.9095519 190 NA -56.4818925 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -112.4220145 -120.4826249 [2,] 11.6620864 -112.4220145 [3,] -96.9674036 11.6620864 [4,] -120.5899857 -96.9674036 [5,] -39.4556096 -120.5899857 [6,] -160.6391667 -39.4556096 [7,] -194.9330993 -160.6391667 [8,] 153.1262367 -194.9330993 [9,] -77.2960547 153.1262367 [10,] -46.2272000 -77.2960547 [11,] 170.5201257 -46.2272000 [12,] -21.1451158 170.5201257 [13,] -70.7883619 -21.1451158 [14,] -151.6396726 -70.7883619 [15,] -91.7270782 -151.6396726 [16,] 142.4538314 -91.7270782 [17,] 36.1066287 142.4538314 [18,] -133.2191241 36.1066287 [19,] 75.7194726 -133.2191241 [20,] 76.4067064 75.7194726 [21,] 150.3506644 76.4067064 [22,] 85.7970591 150.3506644 [23,] -114.1181490 85.7970591 [24,] -48.9739713 -114.1181490 [25,] 35.9235216 -48.9739713 [26,] 65.4292181 35.9235216 [27,] 34.7412837 65.4292181 [28,] 0.1276429 34.7412837 [29,] 127.9073344 0.1276429 [30,] -274.2202000 127.9073344 [31,] 83.4979092 -274.2202000 [32,] 103.7330706 83.4979092 [33,] -119.7436542 103.7330706 [34,] 264.4358030 -119.7436542 [35,] 46.8267560 264.4358030 [36,] 44.8593194 46.8267560 [37,] -91.3497278 44.8593194 [38,] 237.9039975 -91.3497278 [39,] 91.3737373 237.9039975 [40,] 99.1758416 91.3737373 [41,] -192.6565283 99.1758416 [42,] -44.1479426 -192.6565283 [43,] 60.2784539 -44.1479426 [44,] 249.9934743 60.2784539 [45,] 286.8421185 249.9934743 [46,] 65.5951422 286.8421185 [47,] 147.2318726 65.5951422 [48,] -188.2234891 147.2318726 [49,] 313.9357568 -188.2234891 [50,] 153.3833194 313.9357568 [51,] -28.5562847 153.3833194 [52,] 165.8851891 -28.5562847 [53,] 28.1729131 165.8851891 [54,] 168.9636759 28.1729131 [55,] 0.4332030 168.9636759 [56,] -126.9026647 0.4332030 [57,] -114.9935379 -126.9026647 [58,] -148.5325855 -114.9935379 [59,] 2.8888363 -148.5325855 [60,] -16.6531191 2.8888363 [61,] -87.0036011 -16.6531191 [62,] 147.6172188 -87.0036011 [63,] 194.1227912 147.6172188 [64,] 4.7041073 194.1227912 [65,] 111.2146985 4.7041073 [66,] 156.7639257 111.2146985 [67,] 44.4876447 156.7639257 [68,] -126.1105777 44.4876447 [69,] -193.7932772 -126.1105777 [70,] -124.4365726 -193.7932772 [71,] -101.8097413 -124.4365726 [72,] 163.2748210 -101.8097413 [73,] -90.3364964 163.2748210 [74,] -77.2372500 -90.3364964 [75,] -86.6239865 -77.2372500 [76,] -123.7660291 -86.6239865 [77,] -6.3020246 -123.7660291 [78,] 29.7830239 -6.3020246 [79,] -247.3829996 29.7830239 [80,] -18.8875868 -247.3829996 [81,] 147.8680231 -18.8875868 [82,] -241.5586801 147.8680231 [83,] 218.0252352 -241.5586801 [84,] -174.4237687 218.0252352 [85,] -29.8948143 -174.4237687 [86,] -11.5976583 -29.8948143 [87,] -197.0170989 -11.5976583 [88,] 12.9655747 -197.0170989 [89,] -224.6960546 12.9655747 [90,] 81.1503553 -224.6960546 [91,] 5.5175344 81.1503553 [92,] -28.0699162 5.5175344 [93,] 170.8379454 -28.0699162 [94,] -99.6859914 170.8379454 [95,] -114.9199323 -99.6859914 [96,] -93.3869409 -114.9199323 [97,] 38.3338016 -93.3869409 [98,] -142.8752692 38.3338016 [99,] 77.2348430 -142.8752692 [100,] -34.7747158 77.2348430 [101,] 55.2888386 -34.7747158 [102,] -152.6839307 55.2888386 [103,] -68.4192709 -152.6839307 [104,] 72.1373635 -68.4192709 [105,] 116.5298800 72.1373635 [106,] 232.7249452 116.5298800 [107,] -159.7225060 232.7249452 [108,] -21.9736639 -159.7225060 [109,] 27.7929561 -21.9736639 [110,] -136.8358976 27.7929561 [111,] 154.9631226 -136.8358976 [112,] 50.1758690 154.9631226 [113,] -15.3288735 50.1758690 [114,] -40.6958525 -15.3288735 [115,] -113.2885989 -40.6958525 [116,] 105.0974292 -113.2885989 [117,] 152.1901024 105.0974292 [118,] 68.7669871 152.1901024 [119,] -118.7259940 68.7669871 [120,] 222.7411560 -118.7259940 [121,] -39.8414057 222.7411560 [122,] -60.3460177 -39.8414057 [123,] -72.9468790 -60.3460177 [124,] -115.1906158 -72.9468790 [125,] 44.2159538 -115.1906158 [126,] 52.8011253 44.2159538 [127,] -117.7227854 52.8011253 [128,] 91.9029607 -117.7227854 [129,] 126.3246134 91.9029607 [130,] -40.6061764 126.3246134 [131,] -121.3758269 -40.6061764 [132,] 41.1207255 -121.3758269 [133,] -8.9141097 41.1207255 [134,] -59.4132543 -8.9141097 [135,] 90.4543153 -59.4132543 [136,] -89.3491624 90.4543153 [137,] 18.4708449 -89.3491624 [138,] -41.4076651 18.4708449 [139,] 105.5387468 -41.4076651 [140,] -229.7251453 105.5387468 [141,] -52.1234648 -229.7251453 [142,] -54.8503104 -52.1234648 [143,] 118.7472681 -54.8503104 [144,] 85.8585577 118.7472681 [145,] 8.8515266 85.8585577 [146,] -7.2119665 8.8515266 [147,] -75.3207332 -7.2119665 [148,] 142.5813514 -75.3207332 [149,] -60.6930824 142.5813514 [150,] 79.9788621 -60.6930824 [151,] 179.3318584 79.9788621 [152,] -163.3935042 179.3318584 [153,] -335.4444245 -163.3935042 [154,] -2.7064303 -335.4444245 [155,] 166.9042614 -2.7064303 [156,] 17.8307521 166.9042614 [157,] 16.8745046 17.8307521 [158,] 0.6737509 16.8745046 [159,] 129.1047715 0.6737509 [160,] -65.5769314 129.1047715 [161,] 149.1236085 -65.5769314 [162,] -37.9593064 149.1236085 [163,] 99.7310492 -37.9593064 [164,] 29.9013986 99.7310492 [165,] -8.8121028 29.9013986 [166,] -128.5139641 -8.8121028 [167,] -215.9791300 -128.5139641 [168,] 26.3233808 -215.9791300 [169,] 93.4560860 26.3233808 [170,] -24.9594062 93.4560860 [171,] -113.8253841 -24.9594062 [172,] -34.0040178 -113.8253841 [173,] -71.3411257 -34.0040178 [174,] 179.7367767 -71.3411257 [175,] 13.8161848 179.7367767 [176,] -206.1187970 13.8161848 [177,] -192.2549387 -206.1187970 [178,] 169.7979743 -192.2549387 [179,] 75.5069241 169.7979743 [180,] 83.2539814 75.5069241 [181,] -4.6176220 83.2539814 [182,] 55.4468012 -4.6176220 [183,] -9.0100162 55.4468012 [184,] -34.8179496 -9.0100162 [185,] 39.9724783 -34.8179496 [186,] 135.7954432 39.9724783 [187,] 73.3946971 135.7954432 [188,] 16.9095519 73.3946971 [189,] -56.4818925 16.9095519 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -112.4220145 -120.4826249 2 11.6620864 -112.4220145 3 -96.9674036 11.6620864 4 -120.5899857 -96.9674036 5 -39.4556096 -120.5899857 6 -160.6391667 -39.4556096 7 -194.9330993 -160.6391667 8 153.1262367 -194.9330993 9 -77.2960547 153.1262367 10 -46.2272000 -77.2960547 11 170.5201257 -46.2272000 12 -21.1451158 170.5201257 13 -70.7883619 -21.1451158 14 -151.6396726 -70.7883619 15 -91.7270782 -151.6396726 16 142.4538314 -91.7270782 17 36.1066287 142.4538314 18 -133.2191241 36.1066287 19 75.7194726 -133.2191241 20 76.4067064 75.7194726 21 150.3506644 76.4067064 22 85.7970591 150.3506644 23 -114.1181490 85.7970591 24 -48.9739713 -114.1181490 25 35.9235216 -48.9739713 26 65.4292181 35.9235216 27 34.7412837 65.4292181 28 0.1276429 34.7412837 29 127.9073344 0.1276429 30 -274.2202000 127.9073344 31 83.4979092 -274.2202000 32 103.7330706 83.4979092 33 -119.7436542 103.7330706 34 264.4358030 -119.7436542 35 46.8267560 264.4358030 36 44.8593194 46.8267560 37 -91.3497278 44.8593194 38 237.9039975 -91.3497278 39 91.3737373 237.9039975 40 99.1758416 91.3737373 41 -192.6565283 99.1758416 42 -44.1479426 -192.6565283 43 60.2784539 -44.1479426 44 249.9934743 60.2784539 45 286.8421185 249.9934743 46 65.5951422 286.8421185 47 147.2318726 65.5951422 48 -188.2234891 147.2318726 49 313.9357568 -188.2234891 50 153.3833194 313.9357568 51 -28.5562847 153.3833194 52 165.8851891 -28.5562847 53 28.1729131 165.8851891 54 168.9636759 28.1729131 55 0.4332030 168.9636759 56 -126.9026647 0.4332030 57 -114.9935379 -126.9026647 58 -148.5325855 -114.9935379 59 2.8888363 -148.5325855 60 -16.6531191 2.8888363 61 -87.0036011 -16.6531191 62 147.6172188 -87.0036011 63 194.1227912 147.6172188 64 4.7041073 194.1227912 65 111.2146985 4.7041073 66 156.7639257 111.2146985 67 44.4876447 156.7639257 68 -126.1105777 44.4876447 69 -193.7932772 -126.1105777 70 -124.4365726 -193.7932772 71 -101.8097413 -124.4365726 72 163.2748210 -101.8097413 73 -90.3364964 163.2748210 74 -77.2372500 -90.3364964 75 -86.6239865 -77.2372500 76 -123.7660291 -86.6239865 77 -6.3020246 -123.7660291 78 29.7830239 -6.3020246 79 -247.3829996 29.7830239 80 -18.8875868 -247.3829996 81 147.8680231 -18.8875868 82 -241.5586801 147.8680231 83 218.0252352 -241.5586801 84 -174.4237687 218.0252352 85 -29.8948143 -174.4237687 86 -11.5976583 -29.8948143 87 -197.0170989 -11.5976583 88 12.9655747 -197.0170989 89 -224.6960546 12.9655747 90 81.1503553 -224.6960546 91 5.5175344 81.1503553 92 -28.0699162 5.5175344 93 170.8379454 -28.0699162 94 -99.6859914 170.8379454 95 -114.9199323 -99.6859914 96 -93.3869409 -114.9199323 97 38.3338016 -93.3869409 98 -142.8752692 38.3338016 99 77.2348430 -142.8752692 100 -34.7747158 77.2348430 101 55.2888386 -34.7747158 102 -152.6839307 55.2888386 103 -68.4192709 -152.6839307 104 72.1373635 -68.4192709 105 116.5298800 72.1373635 106 232.7249452 116.5298800 107 -159.7225060 232.7249452 108 -21.9736639 -159.7225060 109 27.7929561 -21.9736639 110 -136.8358976 27.7929561 111 154.9631226 -136.8358976 112 50.1758690 154.9631226 113 -15.3288735 50.1758690 114 -40.6958525 -15.3288735 115 -113.2885989 -40.6958525 116 105.0974292 -113.2885989 117 152.1901024 105.0974292 118 68.7669871 152.1901024 119 -118.7259940 68.7669871 120 222.7411560 -118.7259940 121 -39.8414057 222.7411560 122 -60.3460177 -39.8414057 123 -72.9468790 -60.3460177 124 -115.1906158 -72.9468790 125 44.2159538 -115.1906158 126 52.8011253 44.2159538 127 -117.7227854 52.8011253 128 91.9029607 -117.7227854 129 126.3246134 91.9029607 130 -40.6061764 126.3246134 131 -121.3758269 -40.6061764 132 41.1207255 -121.3758269 133 -8.9141097 41.1207255 134 -59.4132543 -8.9141097 135 90.4543153 -59.4132543 136 -89.3491624 90.4543153 137 18.4708449 -89.3491624 138 -41.4076651 18.4708449 139 105.5387468 -41.4076651 140 -229.7251453 105.5387468 141 -52.1234648 -229.7251453 142 -54.8503104 -52.1234648 143 118.7472681 -54.8503104 144 85.8585577 118.7472681 145 8.8515266 85.8585577 146 -7.2119665 8.8515266 147 -75.3207332 -7.2119665 148 142.5813514 -75.3207332 149 -60.6930824 142.5813514 150 79.9788621 -60.6930824 151 179.3318584 79.9788621 152 -163.3935042 179.3318584 153 -335.4444245 -163.3935042 154 -2.7064303 -335.4444245 155 166.9042614 -2.7064303 156 17.8307521 166.9042614 157 16.8745046 17.8307521 158 0.6737509 16.8745046 159 129.1047715 0.6737509 160 -65.5769314 129.1047715 161 149.1236085 -65.5769314 162 -37.9593064 149.1236085 163 99.7310492 -37.9593064 164 29.9013986 99.7310492 165 -8.8121028 29.9013986 166 -128.5139641 -8.8121028 167 -215.9791300 -128.5139641 168 26.3233808 -215.9791300 169 93.4560860 26.3233808 170 -24.9594062 93.4560860 171 -113.8253841 -24.9594062 172 -34.0040178 -113.8253841 173 -71.3411257 -34.0040178 174 179.7367767 -71.3411257 175 13.8161848 179.7367767 176 -206.1187970 13.8161848 177 -192.2549387 -206.1187970 178 169.7979743 -192.2549387 179 75.5069241 169.7979743 180 83.2539814 75.5069241 181 -4.6176220 83.2539814 182 55.4468012 -4.6176220 183 -9.0100162 55.4468012 184 -34.8179496 -9.0100162 185 39.9724783 -34.8179496 186 135.7954432 39.9724783 187 73.3946971 135.7954432 188 16.9095519 73.3946971 189 -56.4818925 16.9095519 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/7a7691258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/85egv1258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9fd2x1258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/103jq21258727037.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11v8l01258727037.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/12omai1258727037.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/13zjah1258727037.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/14mmwl1258727037.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/159znt1258727037.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/16ng0q1258727038.tab") + } > > system("convert tmp/1dk3n1258727037.ps tmp/1dk3n1258727037.png") > system("convert tmp/29a0c1258727037.ps tmp/29a0c1258727037.png") > system("convert tmp/3k9f31258727037.ps tmp/3k9f31258727037.png") > system("convert tmp/48lc11258727037.ps tmp/48lc11258727037.png") > system("convert tmp/5xckn1258727037.ps tmp/5xckn1258727037.png") > system("convert tmp/6btt21258727037.ps tmp/6btt21258727037.png") > system("convert tmp/7a7691258727037.ps tmp/7a7691258727037.png") > system("convert tmp/85egv1258727037.ps tmp/85egv1258727037.png") > system("convert tmp/9fd2x1258727037.ps tmp/9fd2x1258727037.png") > system("convert tmp/103jq21258727037.ps tmp/103jq21258727037.png") > > > proc.time() user system elapsed 5.009 1.817 10.241